Maximum likelihood of phylogenetic networks.
Jin, Guohua; Nakhleh, Luay; Snir, Sagi; Tuller, Tamir
2006-11-01
Horizontal gene transfer (HGT) is believed to be ubiquitous among bacteria, and plays a major role in their genome diversification as well as their ability to develop resistance to antibiotics. In light of its evolutionary significance and implications for human health, developing accurate and efficient methods for detecting and reconstructing HGT is imperative. In this article we provide a new HGT-oriented likelihood framework for many problems that involve phylogeny-based HGT detection and reconstruction. Beside the formulation of various likelihood criteria, we show that most of these problems are NP-hard, and offer heuristics for efficient and accurate reconstruction of HGT under these criteria. We implemented our heuristics and used them to analyze biological as well as synthetic data. In both cases, our criteria and heuristics exhibited very good performance with respect to identifying the correct number of HGT events as well as inferring their correct location on the species tree. Implementation of the criteria as well as heuristics and hardness proofs are available from the authors upon request. Hardness proofs can also be downloaded at http://www.cs.tau.ac.il/~tamirtul/MLNET/Supp-ML.pdf
On the quirks of maximum parsimony and likelihood on phylogenetic networks.
Bryant, Christopher; Fischer, Mareike; Linz, Simone; Semple, Charles
2017-03-21
Maximum parsimony is one of the most frequently-discussed tree reconstruction methods in phylogenetic estimation. However, in recent years it has become more and more apparent that phylogenetic trees are often not sufficient to describe evolution accurately. For instance, processes like hybridization or lateral gene transfer that are commonplace in many groups of organisms and result in mosaic patterns of relationships cannot be represented by a single phylogenetic tree. This is why phylogenetic networks, which can display such events, are becoming of more and more interest in phylogenetic research. It is therefore necessary to extend concepts like maximum parsimony from phylogenetic trees to networks. Several suggestions for possible extensions can be found in recent literature, for instance the softwired and the hardwired parsimony concepts. In this paper, we analyze the so-called big parsimony problem under these two concepts, i.e. we investigate maximum parsimonious networks and analyze their properties. In particular, we show that finding a softwired maximum parsimony network is possible in polynomial time. We also show that the set of maximum parsimony networks for the hardwired definition always contains at least one phylogenetic tree. Lastly, we investigate some parallels of parsimony to different likelihood concepts on phylogenetic networks. Copyright © 2017 Elsevier Ltd. All rights reserved.
Zhou, Xiaofan; Shen, Xing-Xing; Hittinger, Chris Todd
2018-01-01
Abstract The sizes of the data matrices assembled to resolve branches of the tree of life have increased dramatically, motivating the development of programs for fast, yet accurate, inference. For example, several different fast programs have been developed in the very popular maximum likelihood framework, including RAxML/ExaML, PhyML, IQ-TREE, and FastTree. Although these programs are widely used, a systematic evaluation and comparison of their performance using empirical genome-scale data matrices has so far been lacking. To address this question, we evaluated these four programs on 19 empirical phylogenomic data sets with hundreds to thousands of genes and up to 200 taxa with respect to likelihood maximization, tree topology, and computational speed. For single-gene tree inference, we found that the more exhaustive and slower strategies (ten searches per alignment) outperformed faster strategies (one tree search per alignment) using RAxML, PhyML, or IQ-TREE. Interestingly, single-gene trees inferred by the three programs yielded comparable coalescent-based species tree estimations. For concatenation-based species tree inference, IQ-TREE consistently achieved the best-observed likelihoods for all data sets, and RAxML/ExaML was a close second. In contrast, PhyML often failed to complete concatenation-based analyses, whereas FastTree was the fastest but generated lower likelihood values and more dissimilar tree topologies in both types of analyses. Finally, data matrix properties, such as the number of taxa and the strength of phylogenetic signal, sometimes substantially influenced the programs’ relative performance. Our results provide real-world gene and species tree phylogenetic inference benchmarks to inform the design and execution of large-scale phylogenomic data analyses. PMID:29177474
A short proof that phylogenetic tree reconstruction by maximum likelihood is hard.
Roch, Sebastien
2006-01-01
Maximum likelihood is one of the most widely used techniques to infer evolutionary histories. Although it is thought to be intractable, a proof of its hardness has been lacking. Here, we give a short proof that computing the maximum likelihood tree is NP-hard by exploiting a connection between likelihood and parsimony observed by Tuffley and Steel.
A Short Proof that Phylogenetic Tree Reconstruction by Maximum Likelihood is Hard
Roch, S.
2005-01-01
Maximum likelihood is one of the most widely used techniques to infer evolutionary histories. Although it is thought to be intractable, a proof of its hardness has been lacking. Here, we give a short proof that computing the maximum likelihood tree is NP-hard by exploiting a connection between likelihood and parsimony observed by Tuffley and Steel.
On the Quirks of Maximum Parsimony and Likelihood on Phylogenetic Networks
Bryant, Christopher; Fischer, Mareike; Linz, Simone; Semple, Charles
2015-01-01
Maximum parsimony is one of the most frequently-discussed tree reconstruction methods in phylogenetic estimation. However, in recent years it has become more and more apparent that phylogenetic trees are often not sufficient to describe evolution accurately. For instance, processes like hybridization or lateral gene transfer that are commonplace in many groups of organisms and result in mosaic patterns of relationships cannot be represented by a single phylogenetic tree. This is why phylogene...
The phylogenetic likelihood library.
Flouri, T; Izquierdo-Carrasco, F; Darriba, D; Aberer, A J; Nguyen, L-T; Minh, B Q; Von Haeseler, A; Stamatakis, A
2015-03-01
We introduce the Phylogenetic Likelihood Library (PLL), a highly optimized application programming interface for developing likelihood-based phylogenetic inference and postanalysis software. The PLL implements appropriate data structures and functions that allow users to quickly implement common, error-prone, and labor-intensive tasks, such as likelihood calculations, model parameter as well as branch length optimization, and tree space exploration. The highly optimized and parallelized implementation of the phylogenetic likelihood function and a thorough documentation provide a framework for rapid development of scalable parallel phylogenetic software. By example of two likelihood-based phylogenetic codes we show that the PLL improves the sequential performance of current software by a factor of 2-10 while requiring only 1 month of programming time for integration. We show that, when numerical scaling for preventing floating point underflow is enabled, the double precision likelihood calculations in the PLL are up to 1.9 times faster than those in BEAGLE. On an empirical DNA dataset with 2000 taxa the AVX version of PLL is 4 times faster than BEAGLE (scaling enabled and required). The PLL is available at http://www.libpll.org under the GNU General Public License (GPL). © The Author(s) 2014. Published by Oxford University Press, on behalf of the Society of Systematic Biologists.
Lin, Yu; Hu, Fei; Tang, Jijun; Moret, Bernard M E
2013-01-01
The rapid accumulation of whole-genome data has renewed interest in the study of the evolution of genomic architecture, under such events as rearrangements, duplications, losses. Comparative genomics, evolutionary biology, and cancer research all require tools to elucidate the mechanisms, history, and consequences of those evolutionary events, while phylogenetics could use whole-genome data to enhance its picture of the Tree of Life. Current approaches in the area of phylogenetic analysis are limited to very small collections of closely related genomes using low-resolution data (typically a few hundred syntenic blocks); moreover, these approaches typically do not include duplication and loss events. We describe a maximum likelihood (ML) approach for phylogenetic analysis that takes into account genome rearrangements as well as duplications, insertions, and losses. Our approach can handle high-resolution genomes (with 40,000 or more markers) and can use in the same analysis genomes with very different numbers of markers. Because our approach uses a standard ML reconstruction program (RAxML), it scales up to large trees. We present the results of extensive testing on both simulated and real data showing that our approach returns very accurate results very quickly. In particular, we analyze a dataset of 68 high-resolution eukaryotic genomes, with from 3,000 to 42,000 genes, from the eGOB database; the analysis, including bootstrapping, takes just 3 hours on a desktop system and returns a tree in agreement with all well supported branches, while also suggesting resolutions for some disputed placements.
Directory of Open Access Journals (Sweden)
Kodner Robin B
2010-10-01
Full Text Available Abstract Background Likelihood-based phylogenetic inference is generally considered to be the most reliable classification method for unknown sequences. However, traditional likelihood-based phylogenetic methods cannot be applied to large volumes of short reads from next-generation sequencing due to computational complexity issues and lack of phylogenetic signal. "Phylogenetic placement," where a reference tree is fixed and the unknown query sequences are placed onto the tree via a reference alignment, is a way to bring the inferential power offered by likelihood-based approaches to large data sets. Results This paper introduces pplacer, a software package for phylogenetic placement and subsequent visualization. The algorithm can place twenty thousand short reads on a reference tree of one thousand taxa per hour per processor, has essentially linear time and memory complexity in the number of reference taxa, and is easy to run in parallel. Pplacer features calculation of the posterior probability of a placement on an edge, which is a statistically rigorous way of quantifying uncertainty on an edge-by-edge basis. It also can inform the user of the positional uncertainty for query sequences by calculating expected distance between placement locations, which is crucial in the estimation of uncertainty with a well-sampled reference tree. The software provides visualizations using branch thickness and color to represent number of placements and their uncertainty. A simulation study using reads generated from 631 COG alignments shows a high level of accuracy for phylogenetic placement over a wide range of alignment diversity, and the power of edge uncertainty estimates to measure placement confidence. Conclusions Pplacer enables efficient phylogenetic placement and subsequent visualization, making likelihood-based phylogenetics methodology practical for large collections of reads; it is freely available as source code, binaries, and a web service.
Approximate maximum parsimony and ancestral maximum likelihood.
Alon, Noga; Chor, Benny; Pardi, Fabio; Rapoport, Anat
2010-01-01
We explore the maximum parsimony (MP) and ancestral maximum likelihood (AML) criteria in phylogenetic tree reconstruction. Both problems are NP-hard, so we seek approximate solutions. We formulate the two problems as Steiner tree problems under appropriate distances. The gist of our approach is the succinct characterization of Steiner trees for a small number of leaves for the two distances. This enables the use of known Steiner tree approximation algorithms. The approach leads to a 16/9 approximation ratio for AML and asymptotically to a 1.55 approximation ratio for MP.
McGuire, Jimmy A; Witt, Christopher C; Altshuler, Douglas L; Remsen, J V
2007-10-01
Hummingbirds are an important model system in avian biology, but to date the group has been the subject of remarkably few phylogenetic investigations. Here we present partitioned Bayesian and maximum likelihood phylogenetic analyses for 151 of approximately 330 species of hummingbirds and 12 outgroup taxa based on two protein-coding mitochondrial genes (ND2 and ND4), flanking tRNAs, and two nuclear introns (AK1 and BFib). We analyzed these data under several partitioning strategies ranging between unpartitioned and a maximum of nine partitions. In order to select a statistically justified partitioning strategy following partitioned Bayesian analysis, we considered four alternative criteria including Bayes factors, modified versions of the Akaike information criterion for small sample sizes (AIC(c)), Bayesian information criterion (BIC), and a decision-theoretic methodology (DT). Following partitioned maximum likelihood analyses, we selected a best-fitting strategy using hierarchical likelihood ratio tests (hLRTS), the conventional AICc, BIC, and DT, concluding that the most stringent criterion, the performance-based DT, was the most appropriate methodology for selecting amongst partitioning strategies. In the context of our well-resolved and well-supported phylogenetic estimate, we consider the historical biogeography of hummingbirds using ancestral state reconstructions of (1) primary geographic region of occurrence (i.e., South America, Central America, North America, Greater Antilles, Lesser Antilles), (2) Andean or non-Andean geographic distribution, and (3) minimum elevational occurrence. These analyses indicate that the basal hummingbird assemblages originated in the lowlands of South America, that most of the principle clades of hummingbirds (all but Mountain Gems and possibly Bees) originated on this continent, and that there have been many (at least 30) independent invasions of other primary landmasses, especially Central America.
Phylogenetic analysis using parsimony and likelihood methods.
Yang, Z
1996-02-01
The assumptions underlying the maximum-parsimony (MP) method of phylogenetic tree reconstruction were intuitively examined by studying the way the method works. Computer simulations were performed to corroborate the intuitive examination. Parsimony appears to involve very stringent assumptions concerning the process of sequence evolution, such as constancy of substitution rates between nucleotides, constancy of rates across nucleotide sites, and equal branch lengths in the tree. For practical data analysis, the requirement of equal branch lengths means similar substitution rates among lineages (the existence of an approximate molecular clock), relatively long interior branches, and also few species in the data. However, a small amount of evolution is neither a necessary nor a sufficient requirement of the method. The difficulties involved in the application of current statistical estimation theory to tree reconstruction were discussed, and it was suggested that the approach proposed by Felsenstein (1981, J. Mol. Evol. 17: 368-376) for topology estimation, as well as its many variations and extensions, differs fundamentally from the maximum likelihood estimation of a conventional statistical parameter. Evidence was presented showing that the Felsenstein approach does not share the asymptotic efficiency of the maximum likelihood estimator of a statistical parameter. Computer simulations were performed to study the probability that MP recovers the true tree under a hierarchy of models of nucleotide substitution; its performance relative to the likelihood method was especially noted. The results appeared to support the intuitive examination of the assumptions underlying MP. When a simple model of nucleotide substitution was assumed to generate data, the probability that MP recovers the true topology could be as high as, or even higher than, that for the likelihood method. When the assumed model became more complex and realistic, e.g., when substitution rates were
Efficient Detection of Repeating Sites to Accelerate Phylogenetic Likelihood Calculations.
Kobert, K; Stamatakis, A; Flouri, T
2017-03-01
The phylogenetic likelihood function (PLF) is the major computational bottleneck in several applications of evolutionary biology such as phylogenetic inference, species delimitation, model selection, and divergence times estimation. Given the alignment, a tree and the evolutionary model parameters, the likelihood function computes the conditional likelihood vectors for every node of the tree. Vector entries for which all input data are identical result in redundant likelihood operations which, in turn, yield identical conditional values. Such operations can be omitted for improving run-time and, using appropriate data structures, reducing memory usage. We present a fast, novel method for identifying and omitting such redundant operations in phylogenetic likelihood calculations, and assess the performance improvement and memory savings attained by our method. Using empirical and simulated data sets, we show that a prototype implementation of our method yields up to 12-fold speedups and uses up to 78% less memory than one of the fastest and most highly tuned implementations of the PLF currently available. Our method is generic and can seamlessly be integrated into any phylogenetic likelihood implementation. [Algorithms; maximum likelihood; phylogenetic likelihood function; phylogenetics]. © The Author(s) 2016. Published by Oxford University Press, on behalf of the Society of Systematic Biologists.
MXLKID: a maximum likelihood parameter identifier
International Nuclear Information System (INIS)
Gavel, D.T.
1980-07-01
MXLKID (MaXimum LiKelihood IDentifier) is a computer program designed to identify unknown parameters in a nonlinear dynamic system. Using noisy measurement data from the system, the maximum likelihood identifier computes a likelihood function (LF). Identification of system parameters is accomplished by maximizing the LF with respect to the parameters. The main body of this report briefly summarizes the maximum likelihood technique and gives instructions and examples for running the MXLKID program. MXLKID is implemented LRLTRAN on the CDC7600 computer at LLNL. A detailed mathematical description of the algorithm is given in the appendices. 24 figures, 6 tables
Maximum-Likelihood Detection Of Noncoherent CPM
Divsalar, Dariush; Simon, Marvin K.
1993-01-01
Simplified detectors proposed for use in maximum-likelihood-sequence detection of symbols in alphabet of size M transmitted by uncoded, full-response continuous phase modulation over radio channel with additive white Gaussian noise. Structures of receivers derived from particular interpretation of maximum-likelihood metrics. Receivers include front ends, structures of which depends only on M, analogous to those in receivers of coherent CPM. Parts of receivers following front ends have structures, complexity of which would depend on N.
Maximum likelihood estimation for integrated diffusion processes
DEFF Research Database (Denmark)
Baltazar-Larios, Fernando; Sørensen, Michael
We propose a method for obtaining maximum likelihood estimates of parameters in diffusion models when the data is a discrete time sample of the integral of the process, while no direct observations of the process itself are available. The data are, moreover, assumed to be contaminated...... EM-algorithm to obtain maximum likelihood estimates of the parameters in the diffusion model. As part of the algorithm, we use a recent simple method for approximate simulation of diffusion bridges. In simulation studies for the Ornstein-Uhlenbeck process and the CIR process the proposed method works...... by measurement errors. Integrated volatility is an example of this type of observations. Another example is ice-core data on oxygen isotopes used to investigate paleo-temperatures. The data can be viewed as incomplete observations of a model with a tractable likelihood function. Therefore we propose a simulated...
Maximum Parsimony on Phylogenetic networks
2012-01-01
Background Phylogenetic networks are generalizations of phylogenetic trees, that are used to model evolutionary events in various contexts. Several different methods and criteria have been introduced for reconstructing phylogenetic trees. Maximum Parsimony is a character-based approach that infers a phylogenetic tree by minimizing the total number of evolutionary steps required to explain a given set of data assigned on the leaves. Exact solutions for optimizing parsimony scores on phylogenetic trees have been introduced in the past. Results In this paper, we define the parsimony score on networks as the sum of the substitution costs along all the edges of the network; and show that certain well-known algorithms that calculate the optimum parsimony score on trees, such as Sankoff and Fitch algorithms extend naturally for networks, barring conflicting assignments at the reticulate vertices. We provide heuristics for finding the optimum parsimony scores on networks. Our algorithms can be applied for any cost matrix that may contain unequal substitution costs of transforming between different characters along different edges of the network. We analyzed this for experimental data on 10 leaves or fewer with at most 2 reticulations and found that for almost all networks, the bounds returned by the heuristics matched with the exhaustively determined optimum parsimony scores. Conclusion The parsimony score we define here does not directly reflect the cost of the best tree in the network that displays the evolution of the character. However, when searching for the most parsimonious network that describes a collection of characters, it becomes necessary to add additional cost considerations to prefer simpler structures, such as trees over networks. The parsimony score on a network that we describe here takes into account the substitution costs along the additional edges incident on each reticulate vertex, in addition to the substitution costs along the other edges which are
Multi-Channel Maximum Likelihood Pitch Estimation
DEFF Research Database (Denmark)
Christensen, Mads Græsbøll
2012-01-01
In this paper, a method for multi-channel pitch estimation is proposed. The method is a maximum likelihood estimator and is based on a parametric model where the signals in the various channels share the same fundamental frequency but can have different amplitudes, phases, and noise characteristics....... This essentially means that the model allows for different conditions in the various channels, like different signal-to-noise ratios, microphone characteristics and reverberation. Moreover, the method does not assume that a certain array structure is used but rather relies on a more general model and is hence...
Cases in which ancestral maximum likelihood will be confusingly misleading.
Handelman, Tomer; Chor, Benny
2017-05-07
Ancestral maximum likelihood (AML) is a phylogenetic tree reconstruction criteria that "lies between" maximum parsimony (MP) and maximum likelihood (ML). ML has long been known to be statistically consistent. On the other hand, Felsenstein (1978) showed that MP is statistically inconsistent, and even positively misleading: There are cases where the parsimony criteria, applied to data generated according to one tree topology, will be optimized on a different tree topology. The question of weather AML is statistically consistent or not has been open for a long time. Mossel et al. (2009) have shown that AML can "shrink" short tree edges, resulting in a star tree with no internal resolution, which yields a better AML score than the original (resolved) model. This result implies that AML is statistically inconsistent, but not that it is positively misleading, because the star tree is compatible with any other topology. We show that AML is confusingly misleading: For some simple, four taxa (resolved) tree, the ancestral likelihood optimization criteria is maximized on an incorrect (resolved) tree topology, as well as on a star tree (both with specific edge lengths), while the tree with the original, correct topology, has strictly lower ancestral likelihood. Interestingly, the two short edges in the incorrect, resolved tree topology are of length zero, and are not adjacent, so this resolved tree is in fact a simple path. While for MP, the underlying phenomenon can be described as long edge attraction, it turns out that here we have long edge repulsion. Copyright © 2017. Published by Elsevier Ltd.
Maximum Likelihood Reconstruction for Magnetic Resonance Fingerprinting.
Zhao, Bo; Setsompop, Kawin; Ye, Huihui; Cauley, Stephen F; Wald, Lawrence L
2016-08-01
This paper introduces a statistical estimation framework for magnetic resonance (MR) fingerprinting, a recently proposed quantitative imaging paradigm. Within this framework, we present a maximum likelihood (ML) formalism to estimate multiple MR tissue parameter maps directly from highly undersampled, noisy k-space data. A novel algorithm, based on variable splitting, the alternating direction method of multipliers, and the variable projection method, is developed to solve the resulting optimization problem. Representative results from both simulations and in vivo experiments demonstrate that the proposed approach yields significantly improved accuracy in parameter estimation, compared to the conventional MR fingerprinting reconstruction. Moreover, the proposed framework provides new theoretical insights into the conventional approach. We show analytically that the conventional approach is an approximation to the ML reconstruction; more precisely, it is exactly equivalent to the first iteration of the proposed algorithm for the ML reconstruction, provided that a gridding reconstruction is used as an initialization.
Modelling maximum likelihood estimation of availability
International Nuclear Information System (INIS)
Waller, R.A.; Tietjen, G.L.; Rock, G.W.
1975-01-01
Suppose the performance of a nuclear powered electrical generating power plant is continuously monitored to record the sequence of failure and repairs during sustained operation. The purpose of this study is to assess one method of estimating the performance of the power plant when the measure of performance is availability. That is, we determine the probability that the plant is operational at time t. To study the availability of a power plant, we first assume statistical models for the variables, X and Y, which denote the time-to-failure and the time-to-repair variables, respectively. Once those statistical models are specified, the availability, A(t), can be expressed as a function of some or all of their parameters. Usually those parameters are unknown in practice and so A(t) is unknown. This paper discusses the maximum likelihood estimator of A(t) when the time-to-failure model for X is an exponential density with parameter, lambda, and the time-to-repair model for Y is an exponential density with parameter, theta. Under the assumption of exponential models for X and Y, it follows that the instantaneous availability at time t is A(t)=lambda/(lambda+theta)+theta/(lambda+theta)exp[-[(1/lambda)+(1/theta)]t] with t>0. Also, the steady-state availability is A(infinity)=lambda/(lambda+theta). We use the observations from n failure-repair cycles of the power plant, say X 1 , X 2 , ..., Xsub(n), Y 1 , Y 2 , ..., Ysub(n) to present the maximum likelihood estimators of A(t) and A(infinity). The exact sampling distributions for those estimators and some statistical properties are discussed before a simulation model is used to determine 95% simulation intervals for A(t). The methodology is applied to two examples which approximate the operating history of two nuclear power plants. (author)
Neutron spectra unfolding with maximum entropy and maximum likelihood
International Nuclear Information System (INIS)
Itoh, Shikoh; Tsunoda, Toshiharu
1989-01-01
A new unfolding theory has been established on the basis of the maximum entropy principle and the maximum likelihood method. This theory correctly embodies the Poisson statistics of neutron detection, and always brings a positive solution over the whole energy range. Moreover, the theory unifies both problems of overdetermined and of underdetermined. For the latter, the ambiguity in assigning a prior probability, i.e. the initial guess in the Bayesian sense, has become extinct by virtue of the principle. An approximate expression of the covariance matrix for the resultant spectra is also presented. An efficient algorithm to solve the nonlinear system, which appears in the present study, has been established. Results of computer simulation showed the effectiveness of the present theory. (author)
A maximum likelihood framework for protein design
Directory of Open Access Journals (Sweden)
Philippe Hervé
2006-06-01
Full Text Available Abstract Background The aim of protein design is to predict amino-acid sequences compatible with a given target structure. Traditionally envisioned as a purely thermodynamic question, this problem can also be understood in a wider context, where additional constraints are captured by learning the sequence patterns displayed by natural proteins of known conformation. In this latter perspective, however, we still need a theoretical formalization of the question, leading to general and efficient learning methods, and allowing for the selection of fast and accurate objective functions quantifying sequence/structure compatibility. Results We propose a formulation of the protein design problem in terms of model-based statistical inference. Our framework uses the maximum likelihood principle to optimize the unknown parameters of a statistical potential, which we call an inverse potential to contrast with classical potentials used for structure prediction. We propose an implementation based on Markov chain Monte Carlo, in which the likelihood is maximized by gradient descent and is numerically estimated by thermodynamic integration. The fit of the models is evaluated by cross-validation. We apply this to a simple pairwise contact potential, supplemented with a solvent-accessibility term, and show that the resulting models have a better predictive power than currently available pairwise potentials. Furthermore, the model comparison method presented here allows one to measure the relative contribution of each component of the potential, and to choose the optimal number of accessibility classes, which turns out to be much higher than classically considered. Conclusion Altogether, this reformulation makes it possible to test a wide diversity of models, using different forms of potentials, or accounting for other factors than just the constraint of thermodynamic stability. Ultimately, such model-based statistical analyses may help to understand the forces
Maximum likelihood window for time delay estimation
International Nuclear Information System (INIS)
Lee, Young Sup; Yoon, Dong Jin; Kim, Chi Yup
2004-01-01
Time delay estimation for the detection of leak location in underground pipelines is critically important. Because the exact leak location depends upon the precision of the time delay between sensor signals due to leak noise and the speed of elastic waves, the research on the estimation of time delay has been one of the key issues in leak lovating with the time arrival difference method. In this study, an optimal Maximum Likelihood window is considered to obtain a better estimation of the time delay. This method has been proved in experiments, which can provide much clearer and more precise peaks in cross-correlation functions of leak signals. The leak location error has been less than 1 % of the distance between sensors, for example the error was not greater than 3 m for 300 m long underground pipelines. Apart from the experiment, an intensive theoretical analysis in terms of signal processing has been described. The improved leak locating with the suggested method is due to the windowing effect in frequency domain, which offers a weighting in significant frequencies.
Improved Maximum Parsimony Models for Phylogenetic Networks.
Van Iersel, Leo; Jones, Mark; Scornavacca, Celine
2018-05-01
Phylogenetic networks are well suited to represent evolutionary histories comprising reticulate evolution. Several methods aiming at reconstructing explicit phylogenetic networks have been developed in the last two decades. In this article, we propose a new definition of maximum parsimony for phylogenetic networks that permits to model biological scenarios that cannot be modeled by the definitions currently present in the literature (namely, the "hardwired" and "softwired" parsimony). Building on this new definition, we provide several algorithmic results that lay the foundations for new parsimony-based methods for phylogenetic network reconstruction.
Maximum Likelihood and Restricted Likelihood Solutions in Multiple-Method Studies.
Rukhin, Andrew L
2011-01-01
A formulation of the problem of combining data from several sources is discussed in terms of random effects models. The unknown measurement precision is assumed not to be the same for all methods. We investigate maximum likelihood solutions in this model. By representing the likelihood equations as simultaneous polynomial equations, the exact form of the Groebner basis for their stationary points is derived when there are two methods. A parametrization of these solutions which allows their comparison is suggested. A numerical method for solving likelihood equations is outlined, and an alternative to the maximum likelihood method, the restricted maximum likelihood, is studied. In the situation when methods variances are considered to be known an upper bound on the between-method variance is obtained. The relationship between likelihood equations and moment-type equations is also discussed.
Maximum parsimony, substitution model, and probability phylogenetic trees.
Weng, J F; Thomas, D A; Mareels, I
2011-01-01
The problem of inferring phylogenies (phylogenetic trees) is one of the main problems in computational biology. There are three main methods for inferring phylogenies-Maximum Parsimony (MP), Distance Matrix (DM) and Maximum Likelihood (ML), of which the MP method is the most well-studied and popular method. In the MP method the optimization criterion is the number of substitutions of the nucleotides computed by the differences in the investigated nucleotide sequences. However, the MP method is often criticized as it only counts the substitutions observable at the current time and all the unobservable substitutions that really occur in the evolutionary history are omitted. In order to take into account the unobservable substitutions, some substitution models have been established and they are now widely used in the DM and ML methods but these substitution models cannot be used within the classical MP method. Recently the authors proposed a probability representation model for phylogenetic trees and the reconstructed trees in this model are called probability phylogenetic trees. One of the advantages of the probability representation model is that it can include a substitution model to infer phylogenetic trees based on the MP principle. In this paper we explain how to use a substitution model in the reconstruction of probability phylogenetic trees and show the advantage of this approach with examples.
Maximum likelihood estimation of finite mixture model for economic data
Phoong, Seuk-Yen; Ismail, Mohd Tahir
2014-06-01
Finite mixture model is a mixture model with finite-dimension. This models are provides a natural representation of heterogeneity in a finite number of latent classes. In addition, finite mixture models also known as latent class models or unsupervised learning models. Recently, maximum likelihood estimation fitted finite mixture models has greatly drawn statistician's attention. The main reason is because maximum likelihood estimation is a powerful statistical method which provides consistent findings as the sample sizes increases to infinity. Thus, the application of maximum likelihood estimation is used to fit finite mixture model in the present paper in order to explore the relationship between nonlinear economic data. In this paper, a two-component normal mixture model is fitted by maximum likelihood estimation in order to investigate the relationship among stock market price and rubber price for sampled countries. Results described that there is a negative effect among rubber price and stock market price for Malaysia, Thailand, Philippines and Indonesia.
Narrow band interference cancelation in OFDM: Astructured maximum likelihood approach
Sohail, Muhammad Sadiq; Al-Naffouri, Tareq Y.; Al-Ghadhban, Samir N.
2012-01-01
This paper presents a maximum likelihood (ML) approach to mitigate the effect of narrow band interference (NBI) in a zero padded orthogonal frequency division multiplexing (ZP-OFDM) system. The NBI is assumed to be time variant and asynchronous
Penalized Maximum Likelihood Estimation for univariate normal mixture distributions
International Nuclear Information System (INIS)
Ridolfi, A.; Idier, J.
2001-01-01
Due to singularities of the likelihood function, the maximum likelihood approach for the estimation of the parameters of normal mixture models is an acknowledged ill posed optimization problem. Ill posedness is solved by penalizing the likelihood function. In the Bayesian framework, it amounts to incorporating an inverted gamma prior in the likelihood function. A penalized version of the EM algorithm is derived, which is still explicit and which intrinsically assures that the estimates are not singular. Numerical evidence of the latter property is put forward with a test
Tamura, Koichiro; Peterson, Daniel; Peterson, Nicholas; Stecher, Glen; Nei, Masatoshi; Kumar, Sudhir
2011-01-01
Comparative analysis of molecular sequence data is essential for reconstructing the evolutionary histories of species and inferring the nature and extent of selective forces shaping the evolution of genes and species. Here, we announce the release of Molecular Evolutionary Genetics Analysis version 5 (MEGA5), which is a user-friendly software for mining online databases, building sequence alignments and phylogenetic trees, and using methods of evolutionary bioinformatics in basic biology, biomedicine, and evolution. The newest addition in MEGA5 is a collection of maximum likelihood (ML) analyses for inferring evolutionary trees, selecting best-fit substitution models (nucleotide or amino acid), inferring ancestral states and sequences (along with probabilities), and estimating evolutionary rates site-by-site. In computer simulation analyses, ML tree inference algorithms in MEGA5 compared favorably with other software packages in terms of computational efficiency and the accuracy of the estimates of phylogenetic trees, substitution parameters, and rate variation among sites. The MEGA user interface has now been enhanced to be activity driven to make it easier for the use of both beginners and experienced scientists. This version of MEGA is intended for the Windows platform, and it has been configured for effective use on Mac OS X and Linux desktops. It is available free of charge from http://www.megasoftware.net. PMID:21546353
Algorithms of maximum likelihood data clustering with applications
Giada, Lorenzo; Marsili, Matteo
2002-12-01
We address the problem of data clustering by introducing an unsupervised, parameter-free approach based on maximum likelihood principle. Starting from the observation that data sets belonging to the same cluster share a common information, we construct an expression for the likelihood of any possible cluster structure. The likelihood in turn depends only on the Pearson's coefficient of the data. We discuss clustering algorithms that provide a fast and reliable approximation to maximum likelihood configurations. Compared to standard clustering methods, our approach has the advantages that (i) it is parameter free, (ii) the number of clusters need not be fixed in advance and (iii) the interpretation of the results is transparent. In order to test our approach and compare it with standard clustering algorithms, we analyze two very different data sets: time series of financial market returns and gene expression data. We find that different maximization algorithms produce similar cluster structures whereas the outcome of standard algorithms has a much wider variability.
Maximum likelihood estimation of the attenuated ultrasound pulse
DEFF Research Database (Denmark)
Rasmussen, Klaus Bolding
1994-01-01
The attenuated ultrasound pulse is divided into two parts: a stationary basic pulse and a nonstationary attenuation pulse. A standard ARMA model is used for the basic pulse, and a nonstandard ARMA model is derived for the attenuation pulse. The maximum likelihood estimator of the attenuated...
MAXIMUM-LIKELIHOOD-ESTIMATION OF THE ENTROPY OF AN ATTRACTOR
SCHOUTEN, JC; TAKENS, F; VANDENBLEEK, CM
In this paper, a maximum-likelihood estimate of the (Kolmogorov) entropy of an attractor is proposed that can be obtained directly from a time series. Also, the relative standard deviation of the entropy estimate is derived; it is dependent on the entropy and on the number of samples used in the
Adaptive Unscented Kalman Filter using Maximum Likelihood Estimation
DEFF Research Database (Denmark)
Mahmoudi, Zeinab; Poulsen, Niels Kjølstad; Madsen, Henrik
2017-01-01
The purpose of this study is to develop an adaptive unscented Kalman filter (UKF) by tuning the measurement noise covariance. We use the maximum likelihood estimation (MLE) and the covariance matching (CM) method to estimate the noise covariance. The multi-step prediction errors generated...
Multilevel maximum likelihood estimation with application to covariance matrices
Czech Academy of Sciences Publication Activity Database
Turčičová, Marie; Mandel, J.; Eben, Kryštof
Published online: 23 January ( 2018 ) ISSN 0361-0926 R&D Projects: GA ČR GA13-34856S Institutional support: RVO:67985807 Keywords : Fisher information * High dimension * Hierarchical maximum likelihood * Nested parameter spaces * Spectral diagonal covariance model * Sparse inverse covariance model Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.311, year: 2016
GENERALIZATION OF RAYLEIGH MAXIMUM LIKELIHOOD DESPECKLING FILTER USING QUADRILATERAL KERNELS
Directory of Open Access Journals (Sweden)
S. Sridevi
2013-02-01
Full Text Available Speckle noise is the most prevalent noise in clinical ultrasound images. It visibly looks like light and dark spots and deduce the pixel intensity as murkiest. Gazing at fetal ultrasound images, the impact of edge and local fine details are more palpable for obstetricians and gynecologists to carry out prenatal diagnosis of congenital heart disease. A robust despeckling filter has to be contrived to proficiently suppress speckle noise and simultaneously preserve the features. The proposed filter is the generalization of Rayleigh maximum likelihood filter by the exploitation of statistical tools as tuning parameters and use different shapes of quadrilateral kernels to estimate the noise free pixel from neighborhood. The performance of various filters namely Median, Kuwahura, Frost, Homogenous mask filter and Rayleigh maximum likelihood filter are compared with the proposed filter in terms PSNR and image profile. Comparatively the proposed filters surpass the conventional filters.
Maximum Likelihood Compton Polarimetry with the Compton Spectrometer and Imager
Energy Technology Data Exchange (ETDEWEB)
Lowell, A. W.; Boggs, S. E; Chiu, C. L.; Kierans, C. A.; Sleator, C.; Tomsick, J. A.; Zoglauer, A. C. [Space Sciences Laboratory, University of California, Berkeley (United States); Chang, H.-K.; Tseng, C.-H.; Yang, C.-Y. [Institute of Astronomy, National Tsing Hua University, Taiwan (China); Jean, P.; Ballmoos, P. von [IRAP Toulouse (France); Lin, C.-H. [Institute of Physics, Academia Sinica, Taiwan (China); Amman, M. [Lawrence Berkeley National Laboratory (United States)
2017-10-20
Astrophysical polarization measurements in the soft gamma-ray band are becoming more feasible as detectors with high position and energy resolution are deployed. Previous work has shown that the minimum detectable polarization (MDP) of an ideal Compton polarimeter can be improved by ∼21% when an unbinned, maximum likelihood method (MLM) is used instead of the standard approach of fitting a sinusoid to a histogram of azimuthal scattering angles. Here we outline a procedure for implementing this maximum likelihood approach for real, nonideal polarimeters. As an example, we use the recent observation of GRB 160530A with the Compton Spectrometer and Imager. We find that the MDP for this observation is reduced by 20% when the MLM is used instead of the standard method.
Directory of Open Access Journals (Sweden)
Daniel L. Rabosky
2006-01-01
Full Text Available Rates of species origination and extinction can vary over time during evolutionary radiations, and it is possible to reconstruct the history of diversification using molecular phylogenies of extant taxa only. Maximum likelihood methods provide a useful framework for inferring temporal variation in diversification rates. LASER is a package for the R programming environment that implements maximum likelihood methods based on the birth-death process to test whether diversification rates have changed over time. LASER contrasts the likelihood of phylogenetic data under models where diversification rates have changed over time to alternative models where rates have remained constant over time. Major strengths of the package include the ability to detect temporal increases in diversification rates and the inference of diversification parameters under multiple rate-variable models of diversification. The program and associated documentation are freely available from the R package archive at http://cran.r-project.org.
Bayesian interpretation of Generalized empirical likelihood by maximum entropy
Rochet , Paul
2011-01-01
We study a parametric estimation problem related to moment condition models. As an alternative to the generalized empirical likelihood (GEL) and the generalized method of moments (GMM), a Bayesian approach to the problem can be adopted, extending the MEM procedure to parametric moment conditions. We show in particular that a large number of GEL estimators can be interpreted as a maximum entropy solution. Moreover, we provide a more general field of applications by proving the method to be rob...
Maximum Likelihood, Consistency and Data Envelopment Analysis: A Statistical Foundation
Rajiv D. Banker
1993-01-01
This paper provides a formal statistical basis for the efficiency evaluation techniques of data envelopment analysis (DEA). DEA estimators of the best practice monotone increasing and concave production function are shown to be also maximum likelihood estimators if the deviation of actual output from the efficient output is regarded as a stochastic variable with a monotone decreasing probability density function. While the best practice frontier estimator is biased below the theoretical front...
Maximum likelihood convolutional decoding (MCD) performance due to system losses
Webster, L.
1976-01-01
A model for predicting the computational performance of a maximum likelihood convolutional decoder (MCD) operating in a noisy carrier reference environment is described. This model is used to develop a subroutine that will be utilized by the Telemetry Analysis Program to compute the MCD bit error rate. When this computational model is averaged over noisy reference phase errors using a high-rate interpolation scheme, the results are found to agree quite favorably with experimental measurements.
Statistical Bias in Maximum Likelihood Estimators of Item Parameters.
1982-04-01
34 a> E r’r~e r ,C Ie I# ne,..,.rVi rnd Id.,flfv b1 - bindk numb.r) I; ,t-i i-cd I ’ tiie bias in the maximum likelihood ,st i- i;, ’ t iIeiIrs in...NTC, IL 60088 Psychometric Laboratory University of North Carolina I ERIC Facility-Acquisitions Davie Hall 013A 4833 Rugby Avenue Chapel Hill, NC
Maximum likelihood as a common computational framework in tomotherapy
International Nuclear Information System (INIS)
Olivera, G.H.; Shepard, D.M.; Reckwerdt, P.J.; Ruchala, K.; Zachman, J.; Fitchard, E.E.; Mackie, T.R.
1998-01-01
Tomotherapy is a dose delivery technique using helical or axial intensity modulated beams. One of the strengths of the tomotherapy concept is that it can incorporate a number of processes into a single piece of equipment. These processes include treatment optimization planning, dose reconstruction and kilovoltage/megavoltage image reconstruction. A common computational technique that could be used for all of these processes would be very appealing. The maximum likelihood estimator, originally developed for emission tomography, can serve as a useful tool in imaging and radiotherapy. We believe that this approach can play an important role in the processes of optimization planning, dose reconstruction and kilovoltage and/or megavoltage image reconstruction. These processes involve computations that require comparable physical methods. They are also based on equivalent assumptions, and they have similar mathematical solutions. As a result, the maximum likelihood approach is able to provide a common framework for all three of these computational problems. We will demonstrate how maximum likelihood methods can be applied to optimization planning, dose reconstruction and megavoltage image reconstruction in tomotherapy. Results for planning optimization, dose reconstruction and megavoltage image reconstruction will be presented. Strengths and weaknesses of the methodology are analysed. Future directions for this work are also suggested. (author)
MPBoot: fast phylogenetic maximum parsimony tree inference and bootstrap approximation.
Hoang, Diep Thi; Vinh, Le Sy; Flouri, Tomáš; Stamatakis, Alexandros; von Haeseler, Arndt; Minh, Bui Quang
2018-02-02
The nonparametric bootstrap is widely used to measure the branch support of phylogenetic trees. However, bootstrapping is computationally expensive and remains a bottleneck in phylogenetic analyses. Recently, an ultrafast bootstrap approximation (UFBoot) approach was proposed for maximum likelihood analyses. However, such an approach is still missing for maximum parsimony. To close this gap we present MPBoot, an adaptation and extension of UFBoot to compute branch supports under the maximum parsimony principle. MPBoot works for both uniform and non-uniform cost matrices. Our analyses on biological DNA and protein showed that under uniform cost matrices, MPBoot runs on average 4.7 (DNA) to 7 times (protein data) (range: 1.2-20.7) faster than the standard parsimony bootstrap implemented in PAUP*; but 1.6 (DNA) to 4.1 times (protein data) slower than the standard bootstrap with a fast search routine in TNT (fast-TNT). However, for non-uniform cost matrices MPBoot is 5 (DNA) to 13 times (protein data) (range:0.3-63.9) faster than fast-TNT. We note that MPBoot achieves better scores more frequently than PAUP* and fast-TNT. However, this effect is less pronounced if an intensive but slower search in TNT is invoked. Moreover, experiments on large-scale simulated data show that while both PAUP* and TNT bootstrap estimates are too conservative, MPBoot bootstrap estimates appear more unbiased. MPBoot provides an efficient alternative to the standard maximum parsimony bootstrap procedure. It shows favorable performance in terms of run time, the capability of finding a maximum parsimony tree, and high bootstrap accuracy on simulated as well as empirical data sets. MPBoot is easy-to-use, open-source and available at http://www.cibiv.at/software/mpboot .
THESEUS: maximum likelihood superpositioning and analysis of macromolecular structures.
Theobald, Douglas L; Wuttke, Deborah S
2006-09-01
THESEUS is a command line program for performing maximum likelihood (ML) superpositions and analysis of macromolecular structures. While conventional superpositioning methods use ordinary least-squares (LS) as the optimization criterion, ML superpositions provide substantially improved accuracy by down-weighting variable structural regions and by correcting for correlations among atoms. ML superpositioning is robust and insensitive to the specific atoms included in the analysis, and thus it does not require subjective pruning of selected variable atomic coordinates. Output includes both likelihood-based and frequentist statistics for accurate evaluation of the adequacy of a superposition and for reliable analysis of structural similarities and differences. THESEUS performs principal components analysis for analyzing the complex correlations found among atoms within a structural ensemble. ANSI C source code and selected binaries for various computing platforms are available under the GNU open source license from http://monkshood.colorado.edu/theseus/ or http://www.theseus3d.org.
Maximum-likelihood method for numerical inversion of Mellin transform
International Nuclear Information System (INIS)
Iqbal, M.
1997-01-01
A method is described for inverting the Mellin transform which uses an expansion in Laguerre polynomials and converts the Mellin transform to Laplace transform, then the maximum-likelihood regularization method is used to recover the original function of the Mellin transform. The performance of the method is illustrated by the inversion of the test functions available in the literature (J. Inst. Math. Appl., 20 (1977) 73; Math. Comput., 53 (1989) 589). Effectiveness of the method is shown by results obtained through demonstration by means of tables and diagrams
Maximum Likelihood and Bayes Estimation in Randomly Censored Geometric Distribution
Directory of Open Access Journals (Sweden)
Hare Krishna
2017-01-01
Full Text Available In this article, we study the geometric distribution under randomly censored data. Maximum likelihood estimators and confidence intervals based on Fisher information matrix are derived for the unknown parameters with randomly censored data. Bayes estimators are also developed using beta priors under generalized entropy and LINEX loss functions. Also, Bayesian credible and highest posterior density (HPD credible intervals are obtained for the parameters. Expected time on test and reliability characteristics are also analyzed in this article. To compare various estimates developed in the article, a Monte Carlo simulation study is carried out. Finally, for illustration purpose, a randomly censored real data set is discussed.
Elemental composition of cosmic rays using a maximum likelihood method
International Nuclear Information System (INIS)
Ruddick, K.
1996-01-01
We present a progress report on our attempts to determine the composition of cosmic rays in the knee region of the energy spectrum. We have used three different devices to measure properties of the extensive air showers produced by primary cosmic rays: the Soudan 2 underground detector measures the muon flux deep underground, a proportional tube array samples shower density at the surface of the earth, and a Cherenkov array observes light produced high in the atmosphere. We have begun maximum likelihood fits to these measurements with the hope of determining the nuclear mass number A on an event by event basis. (orig.)
Maximum Likelihood Joint Tracking and Association in Strong Clutter
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Leonid I. Perlovsky
2013-01-01
Full Text Available We have developed a maximum likelihood formulation for a joint detection, tracking and association problem. An efficient non-combinatorial algorithm for this problem is developed in case of strong clutter for radar data. By using an iterative procedure of the dynamic logic process “from vague-to-crisp” explained in the paper, the new tracker overcomes the combinatorial complexity of tracking in highly-cluttered scenarios and results in an orders-of-magnitude improvement in signal-to-clutter ratio.
Optimized Large-scale CMB Likelihood and Quadratic Maximum Likelihood Power Spectrum Estimation
Gjerløw, E.; Colombo, L. P. L.; Eriksen, H. K.; Górski, K. M.; Gruppuso, A.; Jewell, J. B.; Plaszczynski, S.; Wehus, I. K.
2015-11-01
We revisit the problem of exact cosmic microwave background (CMB) likelihood and power spectrum estimation with the goal of minimizing computational costs through linear compression. This idea was originally proposed for CMB purposes by Tegmark et al., and here we develop it into a fully functioning computational framework for large-scale polarization analysis, adopting WMAP as a working example. We compare five different linear bases (pixel space, harmonic space, noise covariance eigenvectors, signal-to-noise covariance eigenvectors, and signal-plus-noise covariance eigenvectors) in terms of compression efficiency, and find that the computationally most efficient basis is the signal-to-noise eigenvector basis, which is closely related to the Karhunen-Loeve and Principal Component transforms, in agreement with previous suggestions. For this basis, the information in 6836 unmasked WMAP sky map pixels can be compressed into a smaller set of 3102 modes, with a maximum error increase of any single multipole of 3.8% at ℓ ≤ 32 and a maximum shift in the mean values of a joint distribution of an amplitude-tilt model of 0.006σ. This compression reduces the computational cost of a single likelihood evaluation by a factor of 5, from 38 to 7.5 CPU seconds, and it also results in a more robust likelihood by implicitly regularizing nearly degenerate modes. Finally, we use the same compression framework to formulate a numerically stable and computationally efficient variation of the Quadratic Maximum Likelihood implementation, which requires less than 3 GB of memory and 2 CPU minutes per iteration for ℓ ≤ 32, rendering low-ℓ QML CMB power spectrum analysis fully tractable on a standard laptop.
Reconstructing phylogenetic networks using maximum parsimony.
Nakhleh, Luay; Jin, Guohua; Zhao, Fengmei; Mellor-Crummey, John
2005-01-01
Phylogenies - the evolutionary histories of groups of organisms - are one of the most widely used tools throughout the life sciences, as well as objects of research within systematics, evolutionary biology, epidemiology, etc. Almost every tool devised to date to reconstruct phylogenies produces trees; yet it is widely understood and accepted that trees oversimplify the evolutionary histories of many groups of organims, most prominently bacteria (because of horizontal gene transfer) and plants (because of hybrid speciation). Various methods and criteria have been introduced for phylogenetic tree reconstruction. Parsimony is one of the most widely used and studied criteria, and various accurate and efficient heuristics for reconstructing trees based on parsimony have been devised. Jotun Hein suggested a straightforward extension of the parsimony criterion to phylogenetic networks. In this paper we formalize this concept, and provide the first experimental study of the quality of parsimony as a criterion for constructing and evaluating phylogenetic networks. Our results show that, when extended to phylogenetic networks, the parsimony criterion produces promising results. In a great majority of the cases in our experiments, the parsimony criterion accurately predicts the numbers and placements of non-tree events.
Approximate maximum likelihood estimation for population genetic inference.
Bertl, Johanna; Ewing, Gregory; Kosiol, Carolin; Futschik, Andreas
2017-11-27
In many population genetic problems, parameter estimation is obstructed by an intractable likelihood function. Therefore, approximate estimation methods have been developed, and with growing computational power, sampling-based methods became popular. However, these methods such as Approximate Bayesian Computation (ABC) can be inefficient in high-dimensional problems. This led to the development of more sophisticated iterative estimation methods like particle filters. Here, we propose an alternative approach that is based on stochastic approximation. By moving along a simulated gradient or ascent direction, the algorithm produces a sequence of estimates that eventually converges to the maximum likelihood estimate, given a set of observed summary statistics. This strategy does not sample much from low-likelihood regions of the parameter space, and is fast, even when many summary statistics are involved. We put considerable efforts into providing tuning guidelines that improve the robustness and lead to good performance on problems with high-dimensional summary statistics and a low signal-to-noise ratio. We then investigate the performance of our resulting approach and study its properties in simulations. Finally, we re-estimate parameters describing the demographic history of Bornean and Sumatran orang-utans.
Superfast maximum-likelihood reconstruction for quantum tomography
Shang, Jiangwei; Zhang, Zhengyun; Ng, Hui Khoon
2017-06-01
Conventional methods for computing maximum-likelihood estimators (MLE) often converge slowly in practical situations, leading to a search for simplifying methods that rely on additional assumptions for their validity. In this work, we provide a fast and reliable algorithm for maximum-likelihood reconstruction that avoids this slow convergence. Our method utilizes the state-of-the-art convex optimization scheme, an accelerated projected-gradient method, that allows one to accommodate the quantum nature of the problem in a different way than in the standard methods. We demonstrate the power of our approach by comparing its performance with other algorithms for n -qubit state tomography. In particular, an eight-qubit situation that purportedly took weeks of computation time in 2005 can now be completed in under a minute for a single set of data, with far higher accuracy than previously possible. This refutes the common claim that MLE reconstruction is slow and reduces the need for alternative methods that often come with difficult-to-verify assumptions. In fact, recent methods assuming Gaussian statistics or relying on compressed sensing ideas are demonstrably inapplicable for the situation under consideration here. Our algorithm can be applied to general optimization problems over the quantum state space; the philosophy of projected gradients can further be utilized for optimization contexts with general constraints.
Maximum likelihood versus likelihood-free quantum system identification in the atom maser
International Nuclear Information System (INIS)
Catana, Catalin; Kypraios, Theodore; Guţă, Mădălin
2014-01-01
We consider the problem of estimating a dynamical parameter of a Markovian quantum open system (the atom maser), by performing continuous time measurements in the system's output (outgoing atoms). Two estimation methods are investigated and compared. Firstly, the maximum likelihood estimator (MLE) takes into account the full measurement data and is asymptotically optimal in terms of its mean square error. Secondly, the ‘likelihood-free’ method of approximate Bayesian computation (ABC) produces an approximation of the posterior distribution for a given set of summary statistics, by sampling trajectories at different parameter values and comparing them with the measurement data via chosen statistics. Building on previous results which showed that atom counts are poor statistics for certain values of the Rabi angle, we apply MLE to the full measurement data and estimate its Fisher information. We then select several correlation statistics such as waiting times, distribution of successive identical detections, and use them as input of the ABC algorithm. The resulting posterior distribution follows closely the data likelihood, showing that the selected statistics capture ‘most’ statistical information about the Rabi angle. (paper)
Narrow band interference cancelation in OFDM: Astructured maximum likelihood approach
Sohail, Muhammad Sadiq
2012-06-01
This paper presents a maximum likelihood (ML) approach to mitigate the effect of narrow band interference (NBI) in a zero padded orthogonal frequency division multiplexing (ZP-OFDM) system. The NBI is assumed to be time variant and asynchronous with the frequency grid of the ZP-OFDM system. The proposed structure based technique uses the fact that the NBI signal is sparse as compared to the ZP-OFDM signal in the frequency domain. The structure is also useful in reducing the computational complexity of the proposed method. The paper also presents a data aided approach for improved NBI estimation. The suitability of the proposed method is demonstrated through simulations. © 2012 IEEE.
Preliminary attempt on maximum likelihood tomosynthesis reconstruction of DEI data
International Nuclear Information System (INIS)
Wang Zhentian; Huang Zhifeng; Zhang Li; Kang Kejun; Chen Zhiqiang; Zhu Peiping
2009-01-01
Tomosynthesis is a three-dimension reconstruction method that can remove the effect of superimposition with limited angle projections. It is especially promising in mammography where radiation dose is concerned. In this paper, we propose a maximum likelihood tomosynthesis reconstruction algorithm (ML-TS) on the apparent absorption data of diffraction enhanced imaging (DEI). The motivation of this contribution is to develop a tomosynthesis algorithm in low-dose or noisy circumstances and make DEI get closer to clinic application. The theoretical statistical models of DEI data in physics are analyzed and the proposed algorithm is validated with the experimental data at the Beijing Synchrotron Radiation Facility (BSRF). The results of ML-TS have better contrast compared with the well known 'shift-and-add' algorithm and FBP algorithm. (authors)
Marginal Maximum Likelihood Estimation of Item Response Models in R
Directory of Open Access Journals (Sweden)
Matthew S. Johnson
2007-02-01
Full Text Available Item response theory (IRT models are a class of statistical models used by researchers to describe the response behaviors of individuals to a set of categorically scored items. The most common IRT models can be classified as generalized linear fixed- and/or mixed-effect models. Although IRT models appear most often in the psychological testing literature, researchers in other fields have successfully utilized IRT-like models in a wide variety of applications. This paper discusses the three major methods of estimation in IRT and develops R functions utilizing the built-in capabilities of the R environment to find the marginal maximum likelihood estimates of the generalized partial credit model. The currently available R packages ltm is also discussed.
Maximum likelihood estimation of phase-type distributions
DEFF Research Database (Denmark)
Esparza, Luz Judith R
for both univariate and multivariate cases. Methods like the EM algorithm and Markov chain Monte Carlo are applied for this purpose. Furthermore, this thesis provides explicit formulae for computing the Fisher information matrix for discrete and continuous phase-type distributions, which is needed to find......This work is concerned with the statistical inference of phase-type distributions and the analysis of distributions with rational Laplace transform, known as matrix-exponential distributions. The thesis is focused on the estimation of the maximum likelihood parameters of phase-type distributions...... confidence regions for their estimated parameters. Finally, a new general class of distributions, called bilateral matrix-exponential distributions, is defined. These distributions have the entire real line as domain and can be used, for instance, for modelling. In addition, this class of distributions...
Maximum Likelihood Blood Velocity Estimator Incorporating Properties of Flow Physics
DEFF Research Database (Denmark)
Schlaikjer, Malene; Jensen, Jørgen Arendt
2004-01-01
)-data under investigation. The flow physic properties are exploited in the second term, as the range of velocity values investigated in the cross-correlation analysis are compared to the velocity estimates in the temporal and spatial neighborhood of the signal segment under investigation. The new estimator...... has been compared to the cross-correlation (CC) estimator and the previously developed maximum likelihood estimator (MLE). The results show that the CMLE can handle a larger velocity search range and is capable of estimating even low velocity levels from tissue motion. The CC and the MLE produce...... for the CC and the MLE. When the velocity search range is set to twice the limit of the CC and the MLE, the number of incorrect velocity estimates are 0, 19.1, and 7.2% for the CMLE, CC, and MLE, respectively. The ability to handle a larger search range and estimating low velocity levels was confirmed...
Targeted maximum likelihood estimation for a binary treatment: A tutorial.
Luque-Fernandez, Miguel Angel; Schomaker, Michael; Rachet, Bernard; Schnitzer, Mireille E
2018-04-23
When estimating the average effect of a binary treatment (or exposure) on an outcome, methods that incorporate propensity scores, the G-formula, or targeted maximum likelihood estimation (TMLE) are preferred over naïve regression approaches, which are biased under misspecification of a parametric outcome model. In contrast propensity score methods require the correct specification of an exposure model. Double-robust methods only require correct specification of either the outcome or the exposure model. Targeted maximum likelihood estimation is a semiparametric double-robust method that improves the chances of correct model specification by allowing for flexible estimation using (nonparametric) machine-learning methods. It therefore requires weaker assumptions than its competitors. We provide a step-by-step guided implementation of TMLE and illustrate it in a realistic scenario based on cancer epidemiology where assumptions about correct model specification and positivity (ie, when a study participant had 0 probability of receiving the treatment) are nearly violated. This article provides a concise and reproducible educational introduction to TMLE for a binary outcome and exposure. The reader should gain sufficient understanding of TMLE from this introductory tutorial to be able to apply the method in practice. Extensive R-code is provided in easy-to-read boxes throughout the article for replicability. Stata users will find a testing implementation of TMLE and additional material in the Appendix S1 and at the following GitHub repository: https://github.com/migariane/SIM-TMLE-tutorial. © 2018 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.
Maximum-likelihood estimation of recent shared ancestry (ERSA).
Huff, Chad D; Witherspoon, David J; Simonson, Tatum S; Xing, Jinchuan; Watkins, W Scott; Zhang, Yuhua; Tuohy, Therese M; Neklason, Deborah W; Burt, Randall W; Guthery, Stephen L; Woodward, Scott R; Jorde, Lynn B
2011-05-01
Accurate estimation of recent shared ancestry is important for genetics, evolution, medicine, conservation biology, and forensics. Established methods estimate kinship accurately for first-degree through third-degree relatives. We demonstrate that chromosomal segments shared by two individuals due to identity by descent (IBD) provide much additional information about shared ancestry. We developed a maximum-likelihood method for the estimation of recent shared ancestry (ERSA) from the number and lengths of IBD segments derived from high-density SNP or whole-genome sequence data. We used ERSA to estimate relationships from SNP genotypes in 169 individuals from three large, well-defined human pedigrees. ERSA is accurate to within one degree of relationship for 97% of first-degree through fifth-degree relatives and 80% of sixth-degree and seventh-degree relatives. We demonstrate that ERSA's statistical power approaches the maximum theoretical limit imposed by the fact that distant relatives frequently share no DNA through a common ancestor. ERSA greatly expands the range of relationships that can be estimated from genetic data and is implemented in a freely available software package.
A maximum pseudo-likelihood approach for estimating species trees under the coalescent model
Directory of Open Access Journals (Sweden)
Edwards Scott V
2010-10-01
Full Text Available Abstract Background Several phylogenetic approaches have been developed to estimate species trees from collections of gene trees. However, maximum likelihood approaches for estimating species trees under the coalescent model are limited. Although the likelihood of a species tree under the multispecies coalescent model has already been derived by Rannala and Yang, it can be shown that the maximum likelihood estimate (MLE of the species tree (topology, branch lengths, and population sizes from gene trees under this formula does not exist. In this paper, we develop a pseudo-likelihood function of the species tree to obtain maximum pseudo-likelihood estimates (MPE of species trees, with branch lengths of the species tree in coalescent units. Results We show that the MPE of the species tree is statistically consistent as the number M of genes goes to infinity. In addition, the probability that the MPE of the species tree matches the true species tree converges to 1 at rate O(M -1. The simulation results confirm that the maximum pseudo-likelihood approach is statistically consistent even when the species tree is in the anomaly zone. We applied our method, Maximum Pseudo-likelihood for Estimating Species Trees (MP-EST to a mammal dataset. The four major clades found in the MP-EST tree are consistent with those in the Bayesian concatenation tree. The bootstrap supports for the species tree estimated by the MP-EST method are more reasonable than the posterior probability supports given by the Bayesian concatenation method in reflecting the level of uncertainty in gene trees and controversies over the relationship of four major groups of placental mammals. Conclusions MP-EST can consistently estimate the topology and branch lengths (in coalescent units of the species tree. Although the pseudo-likelihood is derived from coalescent theory, and assumes no gene flow or horizontal gene transfer (HGT, the MP-EST method is robust to a small amount of HGT in the
Parallel implementation of D-Phylo algorithm for maximum likelihood clusters.
Malik, Shamita; Sharma, Dolly; Khatri, Sunil Kumar
2017-03-01
This study explains a newly developed parallel algorithm for phylogenetic analysis of DNA sequences. The newly designed D-Phylo is a more advanced algorithm for phylogenetic analysis using maximum likelihood approach. The D-Phylo while misusing the seeking capacity of k -means keeps away from its real constraint of getting stuck at privately conserved motifs. The authors have tested the behaviour of D-Phylo on Amazon Linux Amazon Machine Image(Hardware Virtual Machine)i2.4xlarge, six central processing unit, 122 GiB memory, 8 × 800 Solid-state drive Elastic Block Store volume, high network performance up to 15 processors for several real-life datasets. Distributing the clusters evenly on all the processors provides us the capacity to accomplish a near direct speed if there should arise an occurrence of huge number of processors.
Cosmic shear measurement with maximum likelihood and maximum a posteriori inference
Hall, Alex; Taylor, Andy
2017-06-01
We investigate the problem of noise bias in maximum likelihood and maximum a posteriori estimators for cosmic shear. We derive the leading and next-to-leading order biases and compute them in the context of galaxy ellipticity measurements, extending previous work on maximum likelihood inference for weak lensing. We show that a large part of the bias on these point estimators can be removed using information already contained in the likelihood when a galaxy model is specified, without the need for external calibration. We test these bias-corrected estimators on simulated galaxy images similar to those expected from planned space-based weak lensing surveys, with promising results. We find that the introduction of an intrinsic shape prior can help with mitigation of noise bias, such that the maximum a posteriori estimate can be made less biased than the maximum likelihood estimate. Second-order terms offer a check on the convergence of the estimators, but are largely subdominant. We show how biases propagate to shear estimates, demonstrating in our simple set-up that shear biases can be reduced by orders of magnitude and potentially to within the requirements of planned space-based surveys at mild signal-to-noise ratio. We find that second-order terms can exhibit significant cancellations at low signal-to-noise ratio when Gaussian noise is assumed, which has implications for inferring the performance of shear-measurement algorithms from simplified simulations. We discuss the viability of our point estimators as tools for lensing inference, arguing that they allow for the robust measurement of ellipticity and shear.
Accelerated maximum likelihood parameter estimation for stochastic biochemical systems
Directory of Open Access Journals (Sweden)
Daigle Bernie J
2012-05-01
Full Text Available Abstract Background A prerequisite for the mechanistic simulation of a biochemical system is detailed knowledge of its kinetic parameters. Despite recent experimental advances, the estimation of unknown parameter values from observed data is still a bottleneck for obtaining accurate simulation results. Many methods exist for parameter estimation in deterministic biochemical systems; methods for discrete stochastic systems are less well developed. Given the probabilistic nature of stochastic biochemical models, a natural approach is to choose parameter values that maximize the probability of the observed data with respect to the unknown parameters, a.k.a. the maximum likelihood parameter estimates (MLEs. MLE computation for all but the simplest models requires the simulation of many system trajectories that are consistent with experimental data. For models with unknown parameters, this presents a computational challenge, as the generation of consistent trajectories can be an extremely rare occurrence. Results We have developed Monte Carlo Expectation-Maximization with Modified Cross-Entropy Method (MCEM2: an accelerated method for calculating MLEs that combines advances in rare event simulation with a computationally efficient version of the Monte Carlo expectation-maximization (MCEM algorithm. Our method requires no prior knowledge regarding parameter values, and it automatically provides a multivariate parameter uncertainty estimate. We applied the method to five stochastic systems of increasing complexity, progressing from an analytically tractable pure-birth model to a computationally demanding model of yeast-polarization. Our results demonstrate that MCEM2 substantially accelerates MLE computation on all tested models when compared to a stand-alone version of MCEM. Additionally, we show how our method identifies parameter values for certain classes of models more accurately than two recently proposed computationally efficient methods
Maximum likelihood positioning algorithm for high-resolution PET scanners
International Nuclear Information System (INIS)
Gross-Weege, Nicolas; Schug, David; Hallen, Patrick; Schulz, Volkmar
2016-01-01
Purpose: In high-resolution positron emission tomography (PET), lightsharing elements are incorporated into typical detector stacks to read out scintillator arrays in which one scintillator element (crystal) is smaller than the size of the readout channel. In order to identify the hit crystal by means of the measured light distribution, a positioning algorithm is required. One commonly applied positioning algorithm uses the center of gravity (COG) of the measured light distribution. The COG algorithm is limited in spatial resolution by noise and intercrystal Compton scatter. The purpose of this work is to develop a positioning algorithm which overcomes this limitation. Methods: The authors present a maximum likelihood (ML) algorithm which compares a set of expected light distributions given by probability density functions (PDFs) with the measured light distribution. Instead of modeling the PDFs by using an analytical model, the PDFs of the proposed ML algorithm are generated assuming a single-gamma-interaction model from measured data. The algorithm was evaluated with a hot-rod phantom measurement acquired with the preclinical HYPERION II D PET scanner. In order to assess the performance with respect to sensitivity, energy resolution, and image quality, the ML algorithm was compared to a COG algorithm which calculates the COG from a restricted set of channels. The authors studied the energy resolution of the ML and the COG algorithm regarding incomplete light distributions (missing channel information caused by detector dead time). Furthermore, the authors investigated the effects of using a filter based on the likelihood values on sensitivity, energy resolution, and image quality. Results: A sensitivity gain of up to 19% was demonstrated in comparison to the COG algorithm for the selected operation parameters. Energy resolution and image quality were on a similar level for both algorithms. Additionally, the authors demonstrated that the performance of the ML
Efficient algorithms for maximum likelihood decoding in the surface code
Bravyi, Sergey; Suchara, Martin; Vargo, Alexander
2014-09-01
We describe two implementations of the optimal error correction algorithm known as the maximum likelihood decoder (MLD) for the two-dimensional surface code with a noiseless syndrome extraction. First, we show how to implement MLD exactly in time O (n2), where n is the number of code qubits. Our implementation uses a reduction from MLD to simulation of matchgate quantum circuits. This reduction however requires a special noise model with independent bit-flip and phase-flip errors. Secondly, we show how to implement MLD approximately for more general noise models using matrix product states (MPS). Our implementation has running time O (nχ3), where χ is a parameter that controls the approximation precision. The key step of our algorithm, borrowed from the density matrix renormalization-group method, is a subroutine for contracting a tensor network on the two-dimensional grid. The subroutine uses MPS with a bond dimension χ to approximate the sequence of tensors arising in the course of contraction. We benchmark the MPS-based decoder against the standard minimum weight matching decoder observing a significant reduction of the logical error probability for χ ≥4.
Maximum likelihood sequence estimation for optical complex direct modulation.
Che, Di; Yuan, Feng; Shieh, William
2017-04-17
Semiconductor lasers are versatile optical transmitters in nature. Through the direct modulation (DM), the intensity modulation is realized by the linear mapping between the injection current and the light power, while various angle modulations are enabled by the frequency chirp. Limited by the direct detection, DM lasers used to be exploited only as 1-D (intensity or angle) transmitters by suppressing or simply ignoring the other modulation. Nevertheless, through the digital coherent detection, simultaneous intensity and angle modulations (namely, 2-D complex DM, CDM) can be realized by a single laser diode. The crucial technique of CDM is the joint demodulation of intensity and differential phase with the maximum likelihood sequence estimation (MLSE), supported by a closed-form discrete signal approximation of frequency chirp to characterize the MLSE transition probability. This paper proposes a statistical method for the transition probability to significantly enhance the accuracy of the chirp model. Using the statistical estimation, we demonstrate the first single-channel 100-Gb/s PAM-4 transmission over 1600-km fiber with only 10G-class DM lasers.
Maximum likelihood estimation for cytogenetic dose-response curves
International Nuclear Information System (INIS)
Frome, E.L; DuFrain, R.J.
1983-10-01
In vitro dose-response curves are used to describe the relation between the yield of dicentric chromosome aberrations and radiation dose for human lymphocytes. The dicentric yields follow the Poisson distribution, and the expected yield depends on both the magnitude and the temporal distribution of the dose for low LET radiation. A general dose-response model that describes this relation has been obtained by Kellerer and Rossi using the theory of dual radiation action. The yield of elementary lesions is kappa[γd + g(t, tau)d 2 ], where t is the time and d is dose. The coefficient of the d 2 term is determined by the recovery function and the temporal mode of irradiation. Two special cases of practical interest are split-dose and continuous exposure experiments, and the resulting models are intrinsically nonlinear in the parameters. A general purpose maximum likelihood estimation procedure is described and illustrated with numerical examples from both experimental designs. Poisson regression analysis is used for estimation, hypothesis testing, and regression diagnostics. Results are discussed in the context of exposure assessment procedures for both acute and chronic human radiation exposure
Maximum likelihood estimation for cytogenetic dose-response curves
International Nuclear Information System (INIS)
Frome, E.L.; DuFrain, R.J.
1986-01-01
In vitro dose-response curves are used to describe the relation between chromosome aberrations and radiation dose for human lymphocytes. The lymphocytes are exposed to low-LET radiation, and the resulting dicentric chromosome aberrations follow the Poisson distribution. The expected yield depends on both the magnitude and the temporal distribution of the dose. A general dose-response model that describes this relation has been presented by Kellerer and Rossi (1972, Current Topics on Radiation Research Quarterly 8, 85-158; 1978, Radiation Research 75, 471-488) using the theory of dual radiation action. Two special cases of practical interest are split-dose and continuous exposure experiments, and the resulting dose-time-response models are intrinsically nonlinear in the parameters. A general-purpose maximum likelihood estimation procedure is described, and estimation for the nonlinear models is illustrated with numerical examples from both experimental designs. Poisson regression analysis is used for estimation, hypothesis testing, and regression diagnostics. Results are discussed in the context of exposure assessment procedures for both acute and chronic human radiation exposure
Maximum likelihood pedigree reconstruction using integer linear programming.
Cussens, James; Bartlett, Mark; Jones, Elinor M; Sheehan, Nuala A
2013-01-01
Large population biobanks of unrelated individuals have been highly successful in detecting common genetic variants affecting diseases of public health concern. However, they lack the statistical power to detect more modest gene-gene and gene-environment interaction effects or the effects of rare variants for which related individuals are ideally required. In reality, most large population studies will undoubtedly contain sets of undeclared relatives, or pedigrees. Although a crude measure of relatedness might sometimes suffice, having a good estimate of the true pedigree would be much more informative if this could be obtained efficiently. Relatives are more likely to share longer haplotypes around disease susceptibility loci and are hence biologically more informative for rare variants than unrelated cases and controls. Distant relatives are arguably more useful for detecting variants with small effects because they are less likely to share masking environmental effects. Moreover, the identification of relatives enables appropriate adjustments of statistical analyses that typically assume unrelatedness. We propose to exploit an integer linear programming optimisation approach to pedigree learning, which is adapted to find valid pedigrees by imposing appropriate constraints. Our method is not restricted to small pedigrees and is guaranteed to return a maximum likelihood pedigree. With additional constraints, we can also search for multiple high-probability pedigrees and thus account for the inherent uncertainty in any particular pedigree reconstruction. The true pedigree is found very quickly by comparison with other methods when all individuals are observed. Extensions to more complex problems seem feasible. © 2012 Wiley Periodicals, Inc.
Maximum likelihood estimation for cytogenetic dose-response curves
Energy Technology Data Exchange (ETDEWEB)
Frome, E.L; DuFrain, R.J.
1983-10-01
In vitro dose-response curves are used to describe the relation between the yield of dicentric chromosome aberrations and radiation dose for human lymphocytes. The dicentric yields follow the Poisson distribution, and the expected yield depends on both the magnitude and the temporal distribution of the dose for low LET radiation. A general dose-response model that describes this relation has been obtained by Kellerer and Rossi using the theory of dual radiation action. The yield of elementary lesions is kappa(..gamma..d + g(t, tau)d/sup 2/), where t is the time and d is dose. The coefficient of the d/sup 2/ term is determined by the recovery function and the temporal mode of irradiation. Two special cases of practical interest are split-dose and continuous exposure experiments, and the resulting models are intrinsically nonlinear in the parameters. A general purpose maximum likelihood estimation procedure is described and illustrated with numerical examples from both experimental designs. Poisson regression analysis is used for estimation, hypothesis testing, and regression diagnostics. Results are discussed in the context of exposure assessment procedures for both acute and chronic human radiation exposure.
Maximum likelihood approach for several stochastic volatility models
International Nuclear Information System (INIS)
Camprodon, Jordi; Perelló, Josep
2012-01-01
Volatility measures the amplitude of price fluctuations. Despite it being one of the most important quantities in finance, volatility is not directly observable. Here we apply a maximum likelihood method which assumes that price and volatility follow a two-dimensional diffusion process where volatility is the stochastic diffusion coefficient of the log-price dynamics. We apply this method to the simplest versions of the expOU, the OU and the Heston stochastic volatility models and we study their performance in terms of the log-price probability, the volatility probability, and its Mean First-Passage Time. The approach has some predictive power on the future returns amplitude by only knowing the current volatility. The assumed models do not consider long-range volatility autocorrelation and the asymmetric return-volatility cross-correlation but the method still yields very naturally these two important stylized facts. We apply the method to different market indices and with a good performance in all cases. (paper)
CSIR Research Space (South Africa)
Kok, S
2012-07-01
Full Text Available continuously as the correlation function hyper-parameters approach zero. Since the global minimizer of the maximum likelihood function is an asymptote in this case, it is unclear if maximum likelihood estimation (MLE) remains valid. Numerical ill...
Directory of Open Access Journals (Sweden)
Shu-Hwa Chen
Full Text Available BACKGROUND: Selecting an appropriate substitution model and deriving a tree topology for a given sequence set are essential in phylogenetic analysis. However, such time consuming, computationally intensive tasks rely on knowledge of substitution model theories and related expertise to run through all possible combinations of several separate programs. To ensure a thorough and efficient analysis and avert tedious manipulations of various programs, this work presents an intuitive framework, the phylogenetic reconstruction with automatic likelihood model selectors (PALM, with convincing, updated algorithms and a best-fit model selection mechanism for seamless phylogenetic analysis. METHODOLOGY: As an integrated framework of ClustalW, PhyML, MODELTEST, ProtTest, and several in-house programs, PALM evaluates the fitness of 56 substitution models for nucleotide sequences and 112 substitution models for protein sequences with scores in various criteria. The input for PALM can be either sequences in FASTA format or a sequence alignment file in PHYLIP format. To accelerate the computing of maximum likelihood and bootstrapping, this work integrates MPICH2/PhyML, PalmMonitor and Palm job controller across several machines with multiple processors and adopts the task parallelism approach. Moreover, an intuitive and interactive web component, PalmTree, is developed for displaying and operating the output tree with options of tree rooting, branches swapping, viewing the branch length values, and viewing bootstrapping score, as well as removing nodes to restart analysis iteratively. SIGNIFICANCE: The workflow of PALM is straightforward and coherent. Via a succinct, user-friendly interface, researchers unfamiliar with phylogenetic analysis can easily use this server to submit sequences, retrieve the output, and re-submit a job based on a previous result if some sequences are to be deleted or added for phylogenetic reconstruction. PALM results in an inference of
Evolutionary analysis of apolipoprotein E by Maximum Likelihood and complex network methods
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Leandro de Jesus Benevides
Full Text Available Abstract Apolipoprotein E (apo E is a human glycoprotein with 299 amino acids, and it is a major component of very low density lipoproteins (VLDL and a group of high-density lipoproteins (HDL. Phylogenetic studies are important to clarify how various apo E proteins are related in groups of organisms and whether they evolved from a common ancestor. Here, we aimed at performing a phylogenetic study on apo E carrying organisms. We employed a classical and robust method, such as Maximum Likelihood (ML, and compared the results using a more recent approach based on complex networks. Thirty-two apo E amino acid sequences were downloaded from NCBI. A clear separation could be observed among three major groups: mammals, fish and amphibians. The results obtained from ML method, as well as from the constructed networks showed two different groups: one with mammals only (C1 and another with fish (C2, and a single node with the single sequence available for an amphibian. The accordance in results from the different methods shows that the complex networks approach is effective in phylogenetic studies. Furthermore, our results revealed the conservation of apo E among animal groups.
Maximum-likelihood estimation of the hyperbolic parameters from grouped observations
DEFF Research Database (Denmark)
Jensen, Jens Ledet
1988-01-01
a least-squares problem. The second procedure Hypesti first approaches the maximum-likelihood estimate by iterating in the profile-log likelihood function for the scale parameter. Close to the maximum of the likelihood function, the estimation is brought to an end by iteration, using all four parameters...
Fast and accurate estimation of the covariance between pairwise maximum likelihood distances
Directory of Open Access Journals (Sweden)
Manuel Gil
2014-09-01
Full Text Available Pairwise evolutionary distances are a model-based summary statistic for a set of molecular sequences. They represent the leaf-to-leaf path lengths of the underlying phylogenetic tree. Estimates of pairwise distances with overlapping paths covary because of shared mutation events. It is desirable to take these covariance structure into account to increase precision in any process that compares or combines distances. This paper introduces a fast estimator for the covariance of two pairwise maximum likelihood distances, estimated under general Markov models. The estimator is based on a conjecture (going back to Nei & Jin, 1989 which links the covariance to path lengths. It is proven here under a simple symmetric substitution model. A simulation shows that the estimator outperforms previously published ones in terms of the mean squared error.
Fast and accurate estimation of the covariance between pairwise maximum likelihood distances.
Gil, Manuel
2014-01-01
Pairwise evolutionary distances are a model-based summary statistic for a set of molecular sequences. They represent the leaf-to-leaf path lengths of the underlying phylogenetic tree. Estimates of pairwise distances with overlapping paths covary because of shared mutation events. It is desirable to take these covariance structure into account to increase precision in any process that compares or combines distances. This paper introduces a fast estimator for the covariance of two pairwise maximum likelihood distances, estimated under general Markov models. The estimator is based on a conjecture (going back to Nei & Jin, 1989) which links the covariance to path lengths. It is proven here under a simple symmetric substitution model. A simulation shows that the estimator outperforms previously published ones in terms of the mean squared error.
Goolsby, Eric W
2017-04-01
Ancestral state reconstruction is a method used to study the evolutionary trajectories of quantitative characters on phylogenies. Although efficient methods for univariate ancestral state reconstruction under a Brownian motion model have been described for at least 25 years, to date no generalization has been described to allow more complex evolutionary models, such as multivariate trait evolution, non-Brownian models, missing data, and within-species variation. Furthermore, even for simple univariate Brownian motion models, most phylogenetic comparative R packages compute ancestral states via inefficient tree rerooting and full tree traversals at each tree node, making ancestral state reconstruction extremely time-consuming for large phylogenies. Here, a computationally efficient method for fast maximum likelihood ancestral state reconstruction of continuous characters is described. The algorithm has linear complexity relative to the number of species and outperforms the fastest existing R implementations by several orders of magnitude. The described algorithm is capable of performing ancestral state reconstruction on a 1,000,000-species phylogeny in fewer than 2 s using a standard laptop, whereas the next fastest R implementation would take several days to complete. The method is generalizable to more complex evolutionary models, such as phylogenetic regression, within-species variation, non-Brownian evolutionary models, and multivariate trait evolution. Because this method enables fast repeated computations on phylogenies of virtually any size, implementation of the described algorithm can drastically alleviate the computational burden of many otherwise prohibitively time-consuming tasks requiring reconstruction of ancestral states, such as phylogenetic imputation of missing data, bootstrapping procedures, Expectation-Maximization algorithms, and Bayesian estimation. The described ancestral state reconstruction algorithm is implemented in the Rphylopars
Ros, B.P.; Bijma, F.; de Munck, J.C.; de Gunst, M.C.M.
2016-01-01
This paper deals with multivariate Gaussian models for which the covariance matrix is a Kronecker product of two matrices. We consider maximum likelihood estimation of the model parameters, in particular of the covariance matrix. There is no explicit expression for the maximum likelihood estimator
Wu, Yufeng
2012-03-01
Incomplete lineage sorting can cause incongruence between the phylogenetic history of genes (the gene tree) and that of the species (the species tree), which can complicate the inference of phylogenies. In this article, I present a new coalescent-based algorithm for species tree inference with maximum likelihood. I first describe an improved method for computing the probability of a gene tree topology given a species tree, which is much faster than an existing algorithm by Degnan and Salter (2005). Based on this method, I develop a practical algorithm that takes a set of gene tree topologies and infers species trees with maximum likelihood. This algorithm searches for the best species tree by starting from initial species trees and performing heuristic search to obtain better trees with higher likelihood. This algorithm, called STELLS (which stands for Species Tree InfErence with Likelihood for Lineage Sorting), has been implemented in a program that is downloadable from the author's web page. The simulation results show that the STELLS algorithm is more accurate than an existing maximum likelihood method for many datasets, especially when there is noise in gene trees. I also show that the STELLS algorithm is efficient and can be applied to real biological datasets. © 2011 The Author. Evolution© 2011 The Society for the Study of Evolution.
Maximum Likelihood Estimation and Inference With Examples in R, SAS and ADMB
Millar, Russell B
2011-01-01
This book takes a fresh look at the popular and well-established method of maximum likelihood for statistical estimation and inference. It begins with an intuitive introduction to the concepts and background of likelihood, and moves through to the latest developments in maximum likelihood methodology, including general latent variable models and new material for the practical implementation of integrated likelihood using the free ADMB software. Fundamental issues of statistical inference are also examined, with a presentation of some of the philosophical debates underlying the choice of statis
Directory of Open Access Journals (Sweden)
Wang Huai-Chun
2009-09-01
Full Text Available Abstract Background The covarion hypothesis of molecular evolution holds that selective pressures on a given amino acid or nucleotide site are dependent on the identity of other sites in the molecule that change throughout time, resulting in changes of evolutionary rates of sites along the branches of a phylogenetic tree. At the sequence level, covarion-like evolution at a site manifests as conservation of nucleotide or amino acid states among some homologs where the states are not conserved in other homologs (or groups of homologs. Covarion-like evolution has been shown to relate to changes in functions at sites in different clades, and, if ignored, can adversely affect the accuracy of phylogenetic inference. Results PROCOV (protein covarion analysis is a software tool that implements a number of previously proposed covarion models of protein evolution for phylogenetic inference in a maximum likelihood framework. Several algorithmic and implementation improvements in this tool over previous versions make computationally expensive tree searches with covarion models more efficient and analyses of large phylogenomic data sets tractable. PROCOV can be used to identify covarion sites by comparing the site likelihoods under the covarion process to the corresponding site likelihoods under a rates-across-sites (RAS process. Those sites with the greatest log-likelihood difference between a 'covarion' and an RAS process were found to be of functional or structural significance in a dataset of bacterial and eukaryotic elongation factors. Conclusion Covarion models implemented in PROCOV may be especially useful for phylogenetic estimation when ancient divergences between sequences have occurred and rates of evolution at sites are likely to have changed over the tree. It can also be used to study lineage-specific functional shifts in protein families that result in changes in the patterns of site variability among subtrees.
Maximum likelihood inference of small trees in the presence of long branches.
Parks, Sarah L; Goldman, Nick
2014-09-01
The statistical basis of maximum likelihood (ML), its robustness, and the fact that it appears to suffer less from biases lead to it being one of the most popular methods for tree reconstruction. Despite its popularity, very few analytical solutions for ML exist, so biases suffered by ML are not well understood. One possible bias is long branch attraction (LBA), a regularly cited term generally used to describe a propensity for long branches to be joined together in estimated trees. Although initially mentioned in connection with inconsistency of parsimony, LBA has been claimed to affect all major phylogenetic reconstruction methods, including ML. Despite the widespread use of this term in the literature, exactly what LBA is and what may be causing it is poorly understood, even for simple evolutionary models and small model trees. Studies looking at LBA have focused on the effect of two long branches on tree reconstruction. However, to understand the effect of two long branches it is also important to understand the effect of just one long branch. If ML struggles to reconstruct one long branch, then this may have an impact on LBA. In this study, we look at the effect of one long branch on three-taxon tree reconstruction. We show that, counterintuitively, long branches are preferentially placed at the tips of the tree. This can be understood through the use of analytical solutions to the ML equation and distance matrix methods. We go on to look at the placement of two long branches on four-taxon trees, showing that there is no attraction between long branches, but that for extreme branch lengths long branches are joined together disproportionally often. These results illustrate that even small model trees are still interesting to help understand how ML phylogenetic reconstruction works, and that LBA is a complicated phenomenon that deserves further study. © The Author(s) 2014. Published by Oxford University Press, on behalf of the Society of Systematic Biologists.
Bias Correction for the Maximum Likelihood Estimate of Ability. Research Report. ETS RR-05-15
Zhang, Jinming
2005-01-01
Lord's bias function and the weighted likelihood estimation method are effective in reducing the bias of the maximum likelihood estimate of an examinee's ability under the assumption that the true item parameters are known. This paper presents simulation studies to determine the effectiveness of these two methods in reducing the bias when the item…
Finite mixture model: A maximum likelihood estimation approach on time series data
Yen, Phoong Seuk; Ismail, Mohd Tahir; Hamzah, Firdaus Mohamad
2014-09-01
Recently, statistician emphasized on the fitting of finite mixture model by using maximum likelihood estimation as it provides asymptotic properties. In addition, it shows consistency properties as the sample sizes increases to infinity. This illustrated that maximum likelihood estimation is an unbiased estimator. Moreover, the estimate parameters obtained from the application of maximum likelihood estimation have smallest variance as compared to others statistical method as the sample sizes increases. Thus, maximum likelihood estimation is adopted in this paper to fit the two-component mixture model in order to explore the relationship between rubber price and exchange rate for Malaysia, Thailand, Philippines and Indonesia. Results described that there is a negative effect among rubber price and exchange rate for all selected countries.
Maximum Likelihood Approach for RFID Tag Set Cardinality Estimation with Detection Errors
DEFF Research Database (Denmark)
Nguyen, Chuyen T.; Hayashi, Kazunori; Kaneko, Megumi
2013-01-01
Abstract Estimation schemes of Radio Frequency IDentification (RFID) tag set cardinality are studied in this paper using Maximum Likelihood (ML) approach. We consider the estimation problem under the model of multiple independent reader sessions with detection errors due to unreliable radio...... is evaluated under dierent system parameters and compared with that of the conventional method via computer simulations assuming flat Rayleigh fading environments and framed-slotted ALOHA based protocol. Keywords RFID tag cardinality estimation maximum likelihood detection error...
Directory of Open Access Journals (Sweden)
Azam Zaka
2014-10-01
Full Text Available This paper is concerned with the modifications of maximum likelihood, moments and percentile estimators of the two parameter Power function distribution. Sampling behavior of the estimators is indicated by Monte Carlo simulation. For some combinations of parameter values, some of the modified estimators appear better than the traditional maximum likelihood, moments and percentile estimators with respect to bias, mean square error and total deviation.
Magis, David; Raiche, Gilles
2010-01-01
In this article the authors focus on the issue of the nonuniqueness of the maximum likelihood (ML) estimator of proficiency level in item response theory (with special attention to logistic models). The usual maximum a posteriori (MAP) method offers a good alternative within that framework; however, this article highlights some drawbacks of its…
Maximum likelihood positioning for gamma-ray imaging detectors with depth of interaction measurement
International Nuclear Information System (INIS)
Lerche, Ch.W.; Ros, A.; Monzo, J.M.; Aliaga, R.J.; Ferrando, N.; Martinez, J.D.; Herrero, V.; Esteve, R.; Gadea, R.; Colom, R.J.; Toledo, J.; Mateo, F.; Sebastia, A.; Sanchez, F.; Benlloch, J.M.
2009-01-01
The center of gravity algorithm leads to strong artifacts for gamma-ray imaging detectors that are based on monolithic scintillation crystals and position sensitive photo-detectors. This is a consequence of using the centroids as position estimates. The fact that charge division circuits can also be used to compute the standard deviation of the scintillation light distribution opens a way out of this drawback. We studied the feasibility of maximum likelihood estimation for computing the true gamma-ray photo-conversion position from the centroids and the standard deviation of the light distribution. The method was evaluated on a test detector that consists of the position sensitive photomultiplier tube H8500 and a monolithic LSO crystal (42mmx42mmx10mm). Spatial resolution was measured for the centroids and the maximum likelihood estimates. The results suggest that the maximum likelihood positioning is feasible and partially removes the strong artifacts of the center of gravity algorithm.
Maximum likelihood positioning for gamma-ray imaging detectors with depth of interaction measurement
Energy Technology Data Exchange (ETDEWEB)
Lerche, Ch.W. [Grupo de Sistemas Digitales, ITACA, Universidad Politecnica de Valencia, 46022 Valencia (Spain)], E-mail: lerche@ific.uv.es; Ros, A. [Grupo de Fisica Medica Nuclear, IFIC, Universidad de Valencia-Consejo Superior de Investigaciones Cientificas, 46980 Paterna (Spain); Monzo, J.M.; Aliaga, R.J.; Ferrando, N.; Martinez, J.D.; Herrero, V.; Esteve, R.; Gadea, R.; Colom, R.J.; Toledo, J.; Mateo, F.; Sebastia, A. [Grupo de Sistemas Digitales, ITACA, Universidad Politecnica de Valencia, 46022 Valencia (Spain); Sanchez, F.; Benlloch, J.M. [Grupo de Fisica Medica Nuclear, IFIC, Universidad de Valencia-Consejo Superior de Investigaciones Cientificas, 46980 Paterna (Spain)
2009-06-01
The center of gravity algorithm leads to strong artifacts for gamma-ray imaging detectors that are based on monolithic scintillation crystals and position sensitive photo-detectors. This is a consequence of using the centroids as position estimates. The fact that charge division circuits can also be used to compute the standard deviation of the scintillation light distribution opens a way out of this drawback. We studied the feasibility of maximum likelihood estimation for computing the true gamma-ray photo-conversion position from the centroids and the standard deviation of the light distribution. The method was evaluated on a test detector that consists of the position sensitive photomultiplier tube H8500 and a monolithic LSO crystal (42mmx42mmx10mm). Spatial resolution was measured for the centroids and the maximum likelihood estimates. The results suggest that the maximum likelihood positioning is feasible and partially removes the strong artifacts of the center of gravity algorithm.
Maximum Likelihood Blind Channel Estimation for Space-Time Coding Systems
Directory of Open Access Journals (Sweden)
Hakan A. Çırpan
2002-05-01
Full Text Available Sophisticated signal processing techniques have to be developed for capacity enhancement of future wireless communication systems. In recent years, space-time coding is proposed to provide significant capacity gains over the traditional communication systems in fading wireless channels. Space-time codes are obtained by combining channel coding, modulation, transmit diversity, and optional receive diversity in order to provide diversity at the receiver and coding gain without sacrificing the bandwidth. In this paper, we consider the problem of blind estimation of space-time coded signals along with the channel parameters. Both conditional and unconditional maximum likelihood approaches are developed and iterative solutions are proposed. The conditional maximum likelihood algorithm is based on iterative least squares with projection whereas the unconditional maximum likelihood approach is developed by means of finite state Markov process modelling. The performance analysis issues of the proposed methods are studied. Finally, some simulation results are presented.
Maximum likelihood estimation of the parameters of nonminimum phase and noncausal ARMA models
DEFF Research Database (Denmark)
Rasmussen, Klaus Bolding
1994-01-01
The well-known prediction-error-based maximum likelihood (PEML) method can only handle minimum phase ARMA models. This paper presents a new method known as the back-filtering-based maximum likelihood (BFML) method, which can handle nonminimum phase and noncausal ARMA models. The BFML method...... is identical to the PEML method in the case of a minimum phase ARMA model, and it turns out that the BFML method incorporates a noncausal ARMA filter with poles outside the unit circle for estimation of the parameters of a causal, nonminimum phase ARMA model...
Maximum likelihood estimation of the position of a radiating source in a waveguide
International Nuclear Information System (INIS)
Hinich, M.J.
1979-01-01
An array of sensors is receiving radiation from a source of interest. The source and the array are in a one- or two-dimensional waveguide. The maximum-likelihood estimators of the coordinates of the source are analyzed under the assumptions that the noise field is Gaussian. The Cramer-Rao lower bound is of the order of the number of modes which define the source excitation function. The results show that the accuracy of the maximum likelihood estimator of source depth using a vertical array in a infinite horizontal waveguide (such as the ocean) is limited by the number of modes detected by the array regardless of the array size
Design of Simplified Maximum-Likelihood Receivers for Multiuser CPM Systems
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Li Bing
2014-01-01
Full Text Available A class of simplified maximum-likelihood receivers designed for continuous phase modulation based multiuser systems is proposed. The presented receiver is built upon a front end employing mismatched filters and a maximum-likelihood detector defined in a low-dimensional signal space. The performance of the proposed receivers is analyzed and compared to some existing receivers. Some schemes are designed to implement the proposed receivers and to reveal the roles of different system parameters. Analysis and numerical results show that the proposed receivers can approach the optimum multiuser receivers with significantly (even exponentially in some cases reduced complexity and marginal performance degradation.
Design of simplified maximum-likelihood receivers for multiuser CPM systems.
Bing, Li; Bai, Baoming
2014-01-01
A class of simplified maximum-likelihood receivers designed for continuous phase modulation based multiuser systems is proposed. The presented receiver is built upon a front end employing mismatched filters and a maximum-likelihood detector defined in a low-dimensional signal space. The performance of the proposed receivers is analyzed and compared to some existing receivers. Some schemes are designed to implement the proposed receivers and to reveal the roles of different system parameters. Analysis and numerical results show that the proposed receivers can approach the optimum multiuser receivers with significantly (even exponentially in some cases) reduced complexity and marginal performance degradation.
Maximum likelihood estimation for Cox's regression model under nested case-control sampling
DEFF Research Database (Denmark)
Scheike, Thomas Harder; Juul, Anders
2004-01-01
-like growth factor I was associated with ischemic heart disease. The study was based on a population of 3784 Danes and 231 cases of ischemic heart disease where controls were matched on age and gender. We illustrate the use of the MLE for these data and show how the maximum likelihood framework can be used......Nested case-control sampling is designed to reduce the costs of large cohort studies. It is important to estimate the parameters of interest as efficiently as possible. We present a new maximum likelihood estimator (MLE) for nested case-control sampling in the context of Cox's proportional hazards...... model. The MLE is computed by the EM-algorithm, which is easy to implement in the proportional hazards setting. Standard errors are estimated by a numerical profile likelihood approach based on EM aided differentiation. The work was motivated by a nested case-control study that hypothesized that insulin...
Maximum likelihood estimation of ancestral codon usage bias parameters in Drosophila
DEFF Research Database (Denmark)
Nielsen, Rasmus; Bauer DuMont, Vanessa L; Hubisz, Melissa J
2007-01-01
: the selection coefficient for optimal codon usage (S), allowing joint maximum likelihood estimation of S and the dN/dS ratio. We apply the method to previously published data from Drosophila melanogaster, Drosophila simulans, and Drosophila yakuba and show, in accordance with previous results, that the D...
Application of the Method of Maximum Likelihood to Identification of Bipedal Walking Robots
Czech Academy of Sciences Publication Activity Database
Dolinský, Kamil; Čelikovský, Sergej
(2017) ISSN 1063-6536 R&D Projects: GA ČR(CZ) GA17-04682S Institutional support: RVO:67985556 Keywords : Control * identification * maximum likelihood (ML) * walking robots Subject RIV: BC - Control Systems Theory Impact factor: 3.882, year: 2016 http://ieeexplore.ieee.org/document/7954032/
Kuhnt, S.
2004-01-01
Observed cell counts in contingency tables are perceived as outliers if they have low probability under an anticipated loglinear Poisson model. New procedures for the identification of such outliers are derived using the classical maximum likelihood estimator and an estimator based on the L1 norm.
John Hogland; Nedret Billor; Nathaniel Anderson
2013-01-01
Discriminant analysis, referred to as maximum likelihood classification within popular remote sensing software packages, is a common supervised technique used by analysts. Polytomous logistic regression (PLR), also referred to as multinomial logistic regression, is an alternative classification approach that is less restrictive, more flexible, and easy to interpret. To...
DEFF Research Database (Denmark)
Borkowski, Robert; Johannisson, Pontus; Wymeersch, Henk
2014-01-01
We perform an experimental investigation of a maximum likelihood-based (ML-based) algorithm for bulk chromatic dispersion estimation for digital coherent receivers operating in uncompensated optical networks. We demonstrate the robustness of the method at low optical signal-to-noise ratio (OSNR...
Casabianca, Jodi M.; Lewis, Charles
2015-01-01
Loglinear smoothing (LLS) estimates the latent trait distribution while making fewer assumptions about its form and maintaining parsimony, thus leading to more precise item response theory (IRT) item parameter estimates than standard marginal maximum likelihood (MML). This article provides the expectation-maximization algorithm for MML estimation…
A simple route to maximum-likelihood estimates of two-locus
Indian Academy of Sciences (India)
Home; Journals; Journal of Genetics; Volume 94; Issue 3. A simple route to maximum-likelihood estimates of two-locus recombination fractions under inequality restrictions. Iain L. Macdonald Philasande Nkalashe. Research Note Volume 94 Issue 3 September 2015 pp 479-481 ...
Monte Carlo Maximum Likelihood Estimation for Generalized Long-Memory Time Series Models
Mesters, G.; Koopman, S.J.; Ooms, M.
2016-01-01
An exact maximum likelihood method is developed for the estimation of parameters in a non-Gaussian nonlinear density function that depends on a latent Gaussian dynamic process with long-memory properties. Our method relies on the method of importance sampling and on a linear Gaussian approximating
Maximum likelihood estimation for Cox's regression model under nested case-control sampling
DEFF Research Database (Denmark)
Scheike, Thomas; Juul, Anders
2004-01-01
Nested case-control sampling is designed to reduce the costs of large cohort studies. It is important to estimate the parameters of interest as efficiently as possible. We present a new maximum likelihood estimator (MLE) for nested case-control sampling in the context of Cox's proportional hazard...
Penfield, Randall D.; Bergeron, Jennifer M.
2005-01-01
This article applies a weighted maximum likelihood (WML) latent trait estimator to the generalized partial credit model (GPCM). The relevant equations required to obtain the WML estimator using the Newton-Raphson algorithm are presented, and a simulation study is described that compared the properties of the WML estimator to those of the maximum…
Maximum Likelihood Dynamic Factor Modeling for Arbitrary "N" and "T" Using SEM
Voelkle, Manuel C.; Oud, Johan H. L.; von Oertzen, Timo; Lindenberger, Ulman
2012-01-01
This article has 3 objectives that build on each other. First, we demonstrate how to obtain maximum likelihood estimates for dynamic factor models (the direct autoregressive factor score model) with arbitrary "T" and "N" by means of structural equation modeling (SEM) and compare the approach to existing methods. Second, we go beyond standard time…
Analysis of Minute Features in Speckled Imagery with Maximum Likelihood Estimation
Directory of Open Access Journals (Sweden)
Alejandro C. Frery
2004-12-01
Full Text Available This paper deals with numerical problems arising when performing maximum likelihood parameter estimation in speckled imagery using small samples. The noise that appears in images obtained with coherent illumination, as is the case of sonar, laser, ultrasound-B, and synthetic aperture radar, is called speckle, and it can neither be assumed Gaussian nor additive. The properties of speckle noise are well described by the multiplicative model, a statistical framework from which stem several important distributions. Amongst these distributions, one is regarded as the universal model for speckled data, namely, the Ã°ÂÂ’Â¢0 law. This paper deals with amplitude data, so the Ã°ÂÂ’Â¢A0 distribution will be used. The literature reports that techniques for obtaining estimates (maximum likelihood, based on moments and on order statistics of the parameters of the Ã°ÂÂ’Â¢A0 distribution require samples of hundreds, even thousands, of observations in order to obtain sensible values. This is verified for maximum likelihood estimation, and a proposal based on alternate optimization is made to alleviate this situation. The proposal is assessed with real and simulated data, showing that the convergence problems are no longer present. A Monte Carlo experiment is devised to estimate the quality of maximum likelihood estimators in small samples, and real data is successfully analyzed with the proposed alternated procedure. Stylized empirical influence functions are computed and used to choose a strategy for computing maximum likelihood estimates that is resistant to outliers.
FPGA Acceleration of the phylogenetic likelihood function for Bayesian MCMC inference methods
Directory of Open Access Journals (Sweden)
Bakos Jason D
2010-04-01
Full Text Available Abstract Background Likelihood (ML-based phylogenetic inference has become a popular method for estimating the evolutionary relationships among species based on genomic sequence data. This method is used in applications such as RAxML, GARLI, MrBayes, PAML, and PAUP. The Phylogenetic Likelihood Function (PLF is an important kernel computation for this method. The PLF consists of a loop with no conditional behavior or dependencies between iterations. As such it contains a high potential for exploiting parallelism using micro-architectural techniques. In this paper, we describe a technique for mapping the PLF and supporting logic onto a Field Programmable Gate Array (FPGA-based co-processor. By leveraging the FPGA's on-chip DSP modules and the high-bandwidth local memory attached to the FPGA, the resultant co-processor can accelerate ML-based methods and outperform state-of-the-art multi-core processors. Results We use the MrBayes 3 tool as a framework for designing our co-processor. For large datasets, we estimate that our accelerated MrBayes, if run on a current-generation FPGA, achieves a 10× speedup relative to software running on a state-of-the-art server-class microprocessor. The FPGA-based implementation achieves its performance by deeply pipelining the likelihood computations, performing multiple floating-point operations in parallel, and through a natural log approximation that is chosen specifically to leverage a deeply pipelined custom architecture. Conclusions Heterogeneous computing, which combines general-purpose processors with special-purpose co-processors such as FPGAs and GPUs, is a promising approach for high-performance phylogeny inference as shown by the growing body of literature in this field. FPGAs in particular are well-suited for this task because of their low power consumption as compared to many-core processors and Graphics Processor Units (GPUs 1.
Fast maximum likelihood estimation of mutation rates using a birth-death process.
Wu, Xiaowei; Zhu, Hongxiao
2015-02-07
Since fluctuation analysis was first introduced by Luria and Delbrück in 1943, it has been widely used to make inference about spontaneous mutation rates in cultured cells. Under certain model assumptions, the probability distribution of the number of mutants that appear in a fluctuation experiment can be derived explicitly, which provides the basis of mutation rate estimation. It has been shown that, among various existing estimators, the maximum likelihood estimator usually demonstrates some desirable properties such as consistency and lower mean squared error. However, its application in real experimental data is often hindered by slow computation of likelihood due to the recursive form of the mutant-count distribution. We propose a fast maximum likelihood estimator of mutation rates, MLE-BD, based on a birth-death process model with non-differential growth assumption. Simulation studies demonstrate that, compared with the conventional maximum likelihood estimator derived from the Luria-Delbrück distribution, MLE-BD achieves substantial improvement on computational speed and is applicable to arbitrarily large number of mutants. In addition, it still retains good accuracy on point estimation. Published by Elsevier Ltd.
Estimation Methods for Non-Homogeneous Regression - Minimum CRPS vs Maximum Likelihood
Gebetsberger, Manuel; Messner, Jakob W.; Mayr, Georg J.; Zeileis, Achim
2017-04-01
Non-homogeneous regression models are widely used to statistically post-process numerical weather prediction models. Such regression models correct for errors in mean and variance and are capable to forecast a full probability distribution. In order to estimate the corresponding regression coefficients, CRPS minimization is performed in many meteorological post-processing studies since the last decade. In contrast to maximum likelihood estimation, CRPS minimization is claimed to yield more calibrated forecasts. Theoretically, both scoring rules used as an optimization score should be able to locate a similar and unknown optimum. Discrepancies might result from a wrong distributional assumption of the observed quantity. To address this theoretical concept, this study compares maximum likelihood and minimum CRPS estimation for different distributional assumptions. First, a synthetic case study shows that, for an appropriate distributional assumption, both estimation methods yield to similar regression coefficients. The log-likelihood estimator is slightly more efficient. A real world case study for surface temperature forecasts at different sites in Europe confirms these results but shows that surface temperature does not always follow the classical assumption of a Gaussian distribution. KEYWORDS: ensemble post-processing, maximum likelihood estimation, CRPS minimization, probabilistic temperature forecasting, distributional regression models
Regularization parameter selection methods for ill-posed Poisson maximum likelihood estimation
International Nuclear Information System (INIS)
Bardsley, Johnathan M; Goldes, John
2009-01-01
In image processing applications, image intensity is often measured via the counting of incident photons emitted by the object of interest. In such cases, image data noise is accurately modeled by a Poisson distribution. This motivates the use of Poisson maximum likelihood estimation for image reconstruction. However, when the underlying model equation is ill-posed, regularization is needed. Regularized Poisson likelihood estimation has been studied extensively by the authors, though a problem of high importance remains: the choice of the regularization parameter. We will present three statistically motivated methods for choosing the regularization parameter, and numerical examples will be presented to illustrate their effectiveness
Dang, Cuong Cao; Lefort, Vincent; Le, Vinh Sy; Le, Quang Si; Gascuel, Olivier
2011-10-01
Amino acid replacement rate matrices are an essential basis of protein studies (e.g. in phylogenetics and alignment). A number of general purpose matrices have been proposed (e.g. JTT, WAG, LG) since the seminal work of Margaret Dayhoff and co-workers. However, it has been shown that matrices specific to certain protein groups (e.g. mitochondrial) or life domains (e.g. viruses) differ significantly from general average matrices, and thus perform better when applied to the data to which they are dedicated. This Web server implements the maximum-likelihood estimation procedure that was used to estimate LG, and provides a number of tools and facilities. Users upload a set of multiple protein alignments from their domain of interest and receive the resulting matrix by email, along with statistics and comparisons with other matrices. A non-parametric bootstrap is performed optionally to assess the variability of replacement rate estimates. Maximum-likelihood trees, inferred using the estimated rate matrix, are also computed optionally for each input alignment. Finely tuned procedures and up-to-date ML software (PhyML 3.0, XRATE) are combined to perform all these heavy calculations on our clusters. http://www.atgc-montpellier.fr/ReplacementMatrix/ olivier.gascuel@lirmm.fr Supplementary data are available at http://www.atgc-montpellier.fr/ReplacementMatrix/
Parallelization of maximum likelihood fits with OpenMP and CUDA
Jarp, S; Leduc, J; Nowak, A; Pantaleo, F
2011-01-01
Data analyses based on maximum likelihood fits are commonly used in the high energy physics community for fitting statistical models to data samples. This technique requires the numerical minimization of the negative log-likelihood function. MINUIT is the most common package used for this purpose in the high energy physics community. The main algorithm in this package, MIGRAD, searches the minimum by using the gradient information. The procedure requires several evaluations of the function, depending on the number of free parameters and their initial values. The whole procedure can be very CPU-time consuming in case of complex functions, with several free parameters, many independent variables and large data samples. Therefore, it becomes particularly important to speed-up the evaluation of the negative log-likelihood function. In this paper we present an algorithm and its implementation which benefits from data vectorization and parallelization (based on OpenMP) and which was also ported to Graphics Processi...
Maximum likelihood pixel labeling using a spatially variant finite mixture model
International Nuclear Information System (INIS)
Gopal, S.S.; Hebert, T.J.
1996-01-01
We propose a spatially-variant mixture model for pixel labeling. Based on this spatially-variant mixture model we derive an expectation maximization algorithm for maximum likelihood estimation of the pixel labels. While most algorithms using mixture models entail the subsequent use of a Bayes classifier for pixel labeling, the proposed algorithm yields maximum likelihood estimates of the labels themselves and results in unambiguous pixel labels. The proposed algorithm is fast, robust, easy to implement, flexible in that it can be applied to any arbitrary image data where the number of classes is known and, most importantly, obviates the need for an explicit labeling rule. The algorithm is evaluated both quantitatively and qualitatively on simulated data and on clinical magnetic resonance images of the human brain
Kelly, D. A.; Fermelia, A.; Lee, G. K. F.
1990-01-01
An adaptive Kalman filter design that utilizes recursive maximum likelihood parameter identification is discussed. At the center of this design is the Kalman filter itself, which has the responsibility for attitude determination. At the same time, the identification algorithm is continually identifying the system parameters. The approach is applicable to nonlinear, as well as linear systems. This adaptive Kalman filter design has much potential for real time implementation, especially considering the fast clock speeds, cache memory and internal RAM available today. The recursive maximum likelihood algorithm is discussed in detail, with special attention directed towards its unique matrix formulation. The procedure for using the algorithm is described along with comments on how this algorithm interacts with the Kalman filter.
International Nuclear Information System (INIS)
Beer, M.
1980-01-01
The maximum likelihood method for the multivariate normal distribution is applied to the case of several individual eigenvalues. Correlated Monte Carlo estimates of the eigenvalue are assumed to follow this prescription and aspects of the assumption are examined. Monte Carlo cell calculations using the SAM-CE and VIM codes for the TRX-1 and TRX-2 benchmark reactors, and SAM-CE full core results are analyzed with this method. Variance reductions of a few percent to a factor of 2 are obtained from maximum likelihood estimation as compared with the simple average and the minimum variance individual eigenvalue. The numerical results verify that the use of sample variances and correlation coefficients in place of the corresponding population statistics still leads to nearly minimum variance estimation for a sufficient number of histories and aggregates
Energy Technology Data Exchange (ETDEWEB)
Singh, Harpreet; Arvind; Dorai, Kavita, E-mail: kavita@iisermohali.ac.in
2016-09-07
Estimation of quantum states is an important step in any quantum information processing experiment. A naive reconstruction of the density matrix from experimental measurements can often give density matrices which are not positive, and hence not physically acceptable. How do we ensure that at all stages of reconstruction, we keep the density matrix positive? Recently a method has been suggested based on maximum likelihood estimation, wherein the density matrix is guaranteed to be positive definite. We experimentally implement this protocol on an NMR quantum information processor. We discuss several examples and compare with the standard method of state estimation. - Highlights: • State estimation using maximum likelihood method was performed on an NMR quantum information processor. • Physically valid density matrices were obtained every time in contrast to standard quantum state tomography. • Density matrices of several different entangled and separable states were reconstructed for two and three qubits.
Estimation of Financial Agent-Based Models with Simulated Maximum Likelihood
Czech Academy of Sciences Publication Activity Database
Kukačka, Jiří; Baruník, Jozef
2017-01-01
Roč. 85, č. 1 (2017), s. 21-45 ISSN 0165-1889 R&D Projects: GA ČR(CZ) GBP402/12/G097 Institutional support: RVO:67985556 Keywords : heterogeneous agent model, * simulated maximum likelihood * switching Subject RIV: AH - Economics OBOR OECD: Finance Impact factor: 1.000, year: 2016 http://library.utia.cas.cz/separaty/2017/E/kukacka-0478481.pdf
Maximum likelihood reconstruction in fully 3D PET via the SAGE algorithm
International Nuclear Information System (INIS)
Ollinger, J.M.; Goggin, A.S.
1996-01-01
The SAGE and ordered subsets algorithms have been proposed as fast methods to compute penalized maximum likelihood estimates in PET. We have implemented both for use in fully 3D PET and completed a preliminary evaluation. The technique used to compute the transition matrix is fully described. The evaluation suggests that the ordered subsets algorithm converges much faster than SAGE, but that it stops short of the optimal solution
Maximum likelihood unit rooting test in the presence GARCH: A new test with increased power
Cook , Steve
2008-01-01
Abstract The literature on testing the unit root hypothesis in the presence of GARCH errors is extended. A new test based upon the combination of local-to-unity detrending and joint maximum likelihood estimation of the autoregressive parameter and GARCH process is presented. The finite sample distribution of the test is derived under alternative decisions regarding the deterministic terms employed. Using Monte Carlo simulation, the newly proposed ML t-test is shown to exhibit incre...
Preliminary application of maximum likelihood method in HL-2A Thomson scattering system
International Nuclear Information System (INIS)
Yao Ke; Huang Yuan; Feng Zhen; Liu Chunhua; Li Enping; Nie Lin
2010-01-01
Maximum likelihood method to process the data of HL-2A Thomson scattering system is presented. Using mathematical statistics, this method maximizes the possibility of the likeness between the theoretical data and the observed data, so that we could get more accurate result. It has been proved to be applicable in comparison with that of the ratios method, and some of the drawbacks in ratios method do not exist in this new one. (authors)
Rahnamaei, Z.; Nematollahi, N.; Farnoosh, R.
2012-01-01
We introduce an alternative skew-slash distribution by using the scale mixture of the exponential power distribution. We derive the properties of this distribution and estimate its parameter by Maximum Likelihood and Bayesian methods. By a simulation study we compute the mentioned estimators and their mean square errors, and we provide an example on real data to demonstrate the modeling strength of the new distribution.
Directory of Open Access Journals (Sweden)
Z. Rahnamaei
2012-01-01
Full Text Available We introduce an alternative skew-slash distribution by using the scale mixture of the exponential power distribution. We derive the properties of this distribution and estimate its parameter by Maximum Likelihood and Bayesian methods. By a simulation study we compute the mentioned estimators and their mean square errors, and we provide an example on real data to demonstrate the modeling strength of the new distribution.
Unbinned maximum likelihood fit for the CP conserving couplings for W + photon production at CDF
International Nuclear Information System (INIS)
Lannon, K.
1994-01-01
We present an unbinned maximum likelihood fit as an alternative to the currently used fit for the CP conserving couplings W plus photon production studied at CDF. We show that a four parameter double exponential fits the E T spectrum of the photon very well. We also show that the fit parameters can be related to and by a second order polynomial. Finally, we discuss various conclusions we have reasoned from our results to the fit so far
Lei, Ning; Chiang, Kwo-Fu; Oudrari, Hassan; Xiong, Xiaoxiong
2011-01-01
Optical sensors aboard Earth orbiting satellites such as the next generation Visible/Infrared Imager/Radiometer Suite (VIIRS) assume that the sensors radiometric response in the Reflective Solar Bands (RSB) is described by a quadratic polynomial, in relating the aperture spectral radiance to the sensor Digital Number (DN) readout. For VIIRS Flight Unit 1, the coefficients are to be determined before launch by an attenuation method, although the linear coefficient will be further determined on-orbit through observing the Solar Diffuser. In determining the quadratic polynomial coefficients by the attenuation method, a Maximum Likelihood approach is applied in carrying out the least-squares procedure. Crucial to the Maximum Likelihood least-squares procedure is the computation of the weight. The weight not only has a contribution from the noise of the sensor s digital count, with an important contribution from digitization error, but also is affected heavily by the mathematical expression used to predict the value of the dependent variable, because both the independent and the dependent variables contain random noise. In addition, model errors have a major impact on the uncertainties of the coefficients. The Maximum Likelihood approach demonstrates the inadequacy of the attenuation method model with a quadratic polynomial for the retrieved spectral radiance. We show that using the inadequate model dramatically increases the uncertainties of the coefficients. We compute the coefficient values and their uncertainties, considering both measurement and model errors.
Determination of point of maximum likelihood in failure domain using genetic algorithms
International Nuclear Information System (INIS)
Obadage, A.S.; Harnpornchai, N.
2006-01-01
The point of maximum likelihood in a failure domain yields the highest value of the probability density function in the failure domain. The maximum-likelihood point thus represents the worst combination of random variables that contribute in the failure event. In this work Genetic Algorithms (GAs) with an adaptive penalty scheme have been proposed as a tool for the determination of the maximum likelihood point. The utilization of only numerical values in the GAs operation makes the algorithms applicable to cases of non-linear and implicit single and multiple limit state function(s). The algorithmic simplicity readily extends its application to higher dimensional problems. When combined with Monte Carlo Simulation, the proposed methodology will reduce the computational complexity and at the same time will enhance the possibility in rare-event analysis under limited computational resources. Since, there is no approximation done in the procedure, the solution obtained is considered accurate. Consequently, GAs can be used as a tool for increasing the computational efficiency in the element and system reliability analyses
Grimm, Guido W.; Renner, Susanne S.; Stamatakis, Alexandros; Hemleben, Vera
2007-01-01
The multi-copy internal transcribed spacer (ITS) region of nuclear ribosomal DNA is widely used to infer phylogenetic relationships among closely related taxa. Here we use maximum likelihood (ML) and splits graph analyses to extract phylogenetic information from ~ 600 mostly cloned ITS sequences, representing 81 species and subspecies of Acer, and both species of its sister Dipteronia. Additional analyses compared sequence motifs in Acer and several hundred Anacardiaceae, Burseraceae, Meliaceae, Rutaceae, and Sapindaceae ITS sequences in GenBank. We also assessed the effects of using smaller data sets of consensus sequences with ambiguity coding (accounting for within-species variation) instead of the full (partly redundant) original sequences. Neighbor-nets and bipartition networks were used to visualize conflict among character state patterns. Species clusters observed in the trees and networks largely agree with morphology-based classifications; of de Jong’s (1994) 16 sections, nine are supported in neighbor-net and bipartition networks, and ten by sequence motifs and the ML tree; of his 19 series, 14 are supported in networks, motifs, and the ML tree. Most nodes had higher bootstrap support with matrices of 105 or 40 consensus sequences than with the original matrix. Within-taxon ITS divergence did not differ between diploid and polyploid Acer, and there was little evidence of differentiated parental ITS haplotypes, suggesting that concerted evolution in Acer acts rapidly. PMID:19455198
Directory of Open Access Journals (Sweden)
Guido W. Grimm
2006-01-01
Full Text Available The multi-copy internal transcribed spacer (ITS region of nuclear ribosomal DNA is widely used to infer phylogenetic relationships among closely related taxa. Here we use maximum likelihood (ML and splits graph analyses to extract phylogenetic information from ~ 600 mostly cloned ITS sequences, representing 81 species and subspecies of Acer, and both species of its sister Dipteronia. Additional analyses compared sequence motifs in Acer and several hundred Anacardiaceae, Burseraceae, Meliaceae, Rutaceae, and Sapindaceae ITS sequences in GenBank. We also assessed the effects of using smaller data sets of consensus sequences with ambiguity coding (accounting for within-species variation instead of the full (partly redundant original sequences. Neighbor-nets and bipartition networks were used to visualize conflict among character state patterns. Species clusters observed in the trees and networks largely agree with morphology-based classifications; of de Jong’s (1994 16 sections, nine are supported in neighbor-net and bipartition networks, and ten by sequence motifs and the ML tree; of his 19 series, 14 are supported in networks, motifs, and the ML tree. Most nodes had higher bootstrap support with matrices of 105 or 40 consensus sequences than with the original matrix. Within-taxon ITS divergence did not differ between diploid and polyploid Acer, and there was little evidence of differentiated parental ITS haplotypes, suggesting that concerted evolution in Acer acts rapidly.
Performance of penalized maximum likelihood in estimation of genetic covariances matrices
Directory of Open Access Journals (Sweden)
Meyer Karin
2011-11-01
Full Text Available Abstract Background Estimation of genetic covariance matrices for multivariate problems comprising more than a few traits is inherently problematic, since sampling variation increases dramatically with the number of traits. This paper investigates the efficacy of regularized estimation of covariance components in a maximum likelihood framework, imposing a penalty on the likelihood designed to reduce sampling variation. In particular, penalties that "borrow strength" from the phenotypic covariance matrix are considered. Methods An extensive simulation study was carried out to investigate the reduction in average 'loss', i.e. the deviation in estimated matrices from the population values, and the accompanying bias for a range of parameter values and sample sizes. A number of penalties are examined, penalizing either the canonical eigenvalues or the genetic covariance or correlation matrices. In addition, several strategies to determine the amount of penalization to be applied, i.e. to estimate the appropriate tuning factor, are explored. Results It is shown that substantial reductions in loss for estimates of genetic covariance can be achieved for small to moderate sample sizes. While no penalty performed best overall, penalizing the variance among the estimated canonical eigenvalues on the logarithmic scale or shrinking the genetic towards the phenotypic correlation matrix appeared most advantageous. Estimating the tuning factor using cross-validation resulted in a loss reduction 10 to 15% less than that obtained if population values were known. Applying a mild penalty, chosen so that the deviation in likelihood from the maximum was non-significant, performed as well if not better than cross-validation and can be recommended as a pragmatic strategy. Conclusions Penalized maximum likelihood estimation provides the means to 'make the most' of limited and precious data and facilitates more stable estimation for multi-dimensional analyses. It should
de Queiroz, K; Poe, S
2001-06-01
Advocates of cladistic parsimony methods have invoked the philosophy of Karl Popper in an attempt to argue for the superiority of those methods over phylogenetic methods based on Ronald Fisher's statistical principle of likelihood. We argue that the concept of likelihood in general, and its application to problems of phylogenetic inference in particular, are highly compatible with Popper's philosophy. Examination of Popper's writings reveals that his concept of corroboration is, in fact, based on likelihood. Moreover, because probabilistic assumptions are necessary for calculating the probabilities that define Popper's corroboration, likelihood methods of phylogenetic inference--with their explicit probabilistic basis--are easily reconciled with his concept. In contrast, cladistic parsimony methods, at least as described by certain advocates of those methods, are less easily reconciled with Popper's concept of corroboration. If those methods are interpreted as lacking probabilistic assumptions, then they are incompatible with corroboration. Conversely, if parsimony methods are to be considered compatible with corroboration, then they must be interpreted as carrying implicit probabilistic assumptions. Thus, the non-probabilistic interpretation of cladistic parsimony favored by some advocates of those methods is contradicted by an attempt by the same authors to justify parsimony methods in terms of Popper's concept of corroboration. In addition to being compatible with Popperian corroboration, the likelihood approach to phylogenetic inference permits researchers to test the assumptions of their analytical methods (models) in a way that is consistent with Popper's ideas about the provisional nature of background knowledge.
Directory of Open Access Journals (Sweden)
Dongming Li
2017-04-01
Full Text Available An adaptive optics (AO system provides real-time compensation for atmospheric turbulence. However, an AO image is usually of poor contrast because of the nature of the imaging process, meaning that the image contains information coming from both out-of-focus and in-focus planes of the object, which also brings about a loss in quality. In this paper, we present a robust multi-frame adaptive optics image restoration algorithm via maximum likelihood estimation. Our proposed algorithm uses a maximum likelihood method with image regularization as the basic principle, and constructs the joint log likelihood function for multi-frame AO images based on a Poisson distribution model. To begin with, a frame selection method based on image variance is applied to the observed multi-frame AO images to select images with better quality to improve the convergence of a blind deconvolution algorithm. Then, by combining the imaging conditions and the AO system properties, a point spread function estimation model is built. Finally, we develop our iterative solutions for AO image restoration addressing the joint deconvolution issue. We conduct a number of experiments to evaluate the performances of our proposed algorithm. Experimental results show that our algorithm produces accurate AO image restoration results and outperforms the current state-of-the-art blind deconvolution methods.
Peters, B. C., Jr.; Walker, H. F.
1975-01-01
New results and insights concerning a previously published iterative procedure for obtaining maximum-likelihood estimates of the parameters for a mixture of normal distributions were discussed. It was shown that the procedure converges locally to the consistent maximum likelihood estimate as long as a specified parameter is bounded between two limits. Bound values were given to yield optimal local convergence.
A New Maximum-Likelihood Change Estimator for Two-Pass SAR Coherent Change Detection.
Energy Technology Data Exchange (ETDEWEB)
Wahl, Daniel E.; Yocky, David A.; Jakowatz, Charles V,
2014-09-01
In this paper, we derive a new optimal change metric to be used in synthetic aperture RADAR (SAR) coherent change detection (CCD). Previous CCD methods tend to produce false alarm states (showing change when there is none) in areas of the image that have a low clutter-to-noise power ratio (CNR). The new estimator does not suffer from this shortcoming. It is a surprisingly simple expression, easy to implement, and is optimal in the maximum-likelihood (ML) sense. The estimator produces very impressive results on the CCD collects that we have tested.
Maximum likelihood based multi-channel isotropic reverberation reduction for hearing aids
DEFF Research Database (Denmark)
Kuklasiński, Adam; Doclo, Simon; Jensen, Søren Holdt
2014-01-01
We propose a multi-channel Wiener filter for speech dereverberation in hearing aids. The proposed algorithm uses joint maximum likelihood estimation of the speech and late reverberation spectral variances, under the assumption that the late reverberant sound field is cylindrically isotropic....... The dereverberation performance of the algorithm is evaluated using computer simulations with realistic hearing aid microphone signals including head-related effects. The algorithm is shown to work well with signals reverberated both by synthetic and by measured room impulse responses, achieving improvements...
Directory of Open Access Journals (Sweden)
Behrooz Attaran
2015-01-01
Full Text Available Rotating machinery is the most common machinery in industry. The root of the faults in rotating machinery is often faulty rolling element bearings. This paper presents a technique using optimized artificial neural network by the Bees Algorithm for automated diagnosis of localized faults in rolling element bearings. The inputs of this technique are a number of features (maximum likelihood estimation values, which are derived from the vibration signals of test data. The results shows that the performance of the proposed optimized system is better than most previous studies, even though it uses only two features. Effectiveness of the above method is illustrated using obtained bearing vibration data.
A theory of timing in scintillation counters based on maximum likelihood estimation
International Nuclear Information System (INIS)
Tomitani, Takehiro
1982-01-01
A theory of timing in scintillation counters based on the maximum likelihood estimation is presented. An optimum filter that minimizes the variance of timing is described. A simple formula to estimate the variance of timing is presented as a function of photoelectron number, scintillation decay constant and the single electron transit time spread in the photomultiplier. The present method was compared with the theory by E. Gatti and V. Svelto. The proposed method was applied to two simple models and rough estimations of potential time resolution of several scintillators are given. The proposed method is applicable to the timing in Cerenkov counters and semiconductor detectors as well. (author)
DEFF Research Database (Denmark)
Silver, Jeremy D; Ritchie, Matthew E; Smyth, Gordon K
2009-01-01
exponentially distributed, representing background noise and signal, respectively. Using a saddle-point approximation, Ritchie and others (2007) found normexp to be the best background correction method for 2-color microarray data. This article develops the normexp method further by improving the estimation...... is developed for exact maximum likelihood estimation (MLE) using high-quality optimization software and using the saddle-point estimates as starting values. "MLE" is shown to outperform heuristic estimators proposed by other authors, both in terms of estimation accuracy and in terms of performance on real data...
A Fast Algorithm for Maximum Likelihood Estimation of Harmonic Chirp Parameters
DEFF Research Database (Denmark)
Jensen, Tobias Lindstrøm; Nielsen, Jesper Kjær; Jensen, Jesper Rindom
2017-01-01
. A statistically efficient estimator for extracting the parameters of the harmonic chirp model in additive white Gaussian noise is the maximum likelihood (ML) estimator which recently has been demonstrated to be robust to noise and accurate --- even when the model order is unknown. The main drawback of the ML......The analysis of (approximately) periodic signals is an important element in numerous applications. One generalization of standard periodic signals often occurring in practice are harmonic chirp signals where the instantaneous frequency increases/decreases linearly as a function of time...
A maximum-likelihood reconstruction algorithm for tomographic gamma-ray nondestructive assay
International Nuclear Information System (INIS)
Prettyman, T.H.; Estep, R.J.; Cole, R.A.; Sheppard, G.A.
1994-01-01
A new tomographic reconstruction algorithm for nondestructive assay with high resolution gamma-ray spectroscopy (HRGS) is presented. The reconstruction problem is formulated using a maximum-likelihood approach in which the statistical structure of both the gross and continuum measurements used to determine the full-energy response in HRGS is precisely modeled. An accelerated expectation-maximization algorithm is used to determine the optimal solution. The algorithm is applied to safeguards and environmental assays of large samples (for example, 55-gal. drums) in which high continuum levels caused by Compton scattering are routinely encountered. Details of the implementation of the algorithm and a comparative study of the algorithm's performance are presented
Application of the method of maximum likelihood to the determination of cepheid radii
International Nuclear Information System (INIS)
Balona, L.A.
1977-01-01
A method is described whereby the radius of any pulsating star can be obtained by applying the Principle of Maximum Likelihood. The relative merits of this method and of the usual Baade-Wesselink method are discussed in an Appendix. The new method is applied to 54 well-observed cepheids which include a number of spectroscopic binaries and two W Vir stars. An empirical period-radius relation is constructed and discussed in terms of two recent period-luminosity-colour calibrations. It is shown that the new method gives radii with an error of no more than 10 per cent. (author)
International Nuclear Information System (INIS)
Croce, R P; Demma, Th; Longo, M; Marano, S; Matta, V; Pierro, V; Pinto, I M
2003-01-01
The cumulative distribution of the supremum of a set (bank) of correlators is investigated in the context of maximum likelihood detection of gravitational wave chirps from coalescing binaries with unknown parameters. Accurate (lower-bound) approximants are introduced based on a suitable generalization of previous results by Mohanty. Asymptotic properties (in the limit where the number of correlators goes to infinity) are highlighted. The validity of numerical simulations made on small-size banks is extended to banks of any size, via a Gaussian correlation inequality
Two-Stage Maximum Likelihood Estimation (TSMLE for MT-CDMA Signals in the Indoor Environment
Directory of Open Access Journals (Sweden)
Sesay Abu B
2004-01-01
Full Text Available This paper proposes a two-stage maximum likelihood estimation (TSMLE technique suited for multitone code division multiple access (MT-CDMA system. Here, an analytical framework is presented in the indoor environment for determining the average bit error rate (BER of the system, over Rayleigh and Ricean fading channels. The analytical model is derived for quadrature phase shift keying (QPSK modulation technique by taking into account the number of tones, signal bandwidth (BW, bit rate, and transmission power. Numerical results are presented to validate the analysis, and to justify the approximations made therein. Moreover, these results are shown to agree completely with those obtained by simulation.
Directory of Open Access Journals (Sweden)
Lester L. Yuan
2007-06-01
Full Text Available This paper provides a brief introduction to the R package bio.infer, a set of scripts that facilitates the use of maximum likelihood (ML methods for predicting environmental conditions from assemblage composition. Environmental conditions can often be inferred from only biological data, and these inferences are useful when other sources of data are unavailable. ML prediction methods are statistically rigorous and applicable to a broader set of problems than more commonly used weighted averaging techniques. However, ML methods require a substantially greater investment of time to program algorithms and to perform computations. This package is designed to reduce the effort required to apply ML prediction methods.
The unfolding of NaI(Tl) γ-ray spectrum based on maximum likelihood method
International Nuclear Information System (INIS)
Zhang Qingxian; Ge Liangquan; Gu Yi; Zeng Guoqiang; Lin Yanchang; Wang Guangxi
2011-01-01
NaI(Tl) detectors, having a good detection efficiency, are used to detect gamma rays in field surveys. But the poor energy resolution hinders their applications, despite the use of traditional methods to resolve the overlapped gamma-ray peaks. In this paper, the maximum likelihood (ML) solution is used to resolve the spectrum. The ML method,which is capable of decomposing the peaks in energy difference of over 2/3 FWHM, is applied to scale NaI(Tl) the spectrometer. The result shows that the net area is in proportion to the content of isotopes and the precision of scaling is better than the stripping ration method. (authors)
Directory of Open Access Journals (Sweden)
Maja Olsbjerg
2015-10-01
Full Text Available Item response theory models are often applied when a number items are used to measure a unidimensional latent variable. Originally proposed and used within educational research, they are also used when focus is on physical functioning or psychological wellbeing. Modern applications often need more general models, typically models for multidimensional latent variables or longitudinal models for repeated measurements. This paper describes a SAS macro that fits two-dimensional polytomous Rasch models using a specification of the model that is sufficiently flexible to accommodate longitudinal Rasch models. The macro estimates item parameters using marginal maximum likelihood estimation. A graphical presentation of item characteristic curves is included.
Maximum likelihood reconstruction for pinhole SPECT with a displaced center-of-rotation
International Nuclear Information System (INIS)
Li, J.; Jaszczak, R.J.; Coleman, R.E.
1995-01-01
In this paper, the authors describe the implementation of a maximum likelihood (ML), algorithm using expectation maximization (EM) for pin-hole SPECT with a displaced center-of-rotation. A ray-tracing technique is used in implementing the ML-EM algorithm. The proposed ML-EM algorithm is able to correct the center of rotation displacement which can be characterized by two orthogonal components. The algorithm is tested using experimentally acquired data, and the results demonstrate that the pinhole ML-EM algorithm is able to correct artifacts associated with the center-of-rotation displacement
Maximum likelihood approach to “informed” Sound Source Localization for Hearing Aid applications
DEFF Research Database (Denmark)
Farmani, Mojtaba; Pedersen, Michael Syskind; Tan, Zheng-Hua
2015-01-01
Most state-of-the-art Sound Source Localization (SSL) algorithms have been proposed for applications which are "uninformed'' about the target sound content; however, utilizing a wireless microphone worn by a target talker, enables recent Hearing Aid Systems (HASs) to access to an almost noise......-free sound signal of the target talker at the HAS via the wireless connection. Therefore, in this paper, we propose a maximum likelihood (ML) approach, which we call MLSSL, to estimate the Direction of Arrival (DoA) of the target signal given access to the target signal content. Compared with other "informed...
Directory of Open Access Journals (Sweden)
K. Yao
2007-12-01
Full Text Available We investigate the maximum likelihood (ML direction-of-arrival (DOA estimation of multiple wideband sources in the presence of unknown nonuniform sensor noise. New closed-form expression for the direction estimation CramÃƒÂ©r-Rao-Bound (CRB has been derived. The performance of the conventional wideband uniform ML estimator under nonuniform noise has been studied. In order to mitigate the performance degradation caused by the nonuniformity of the noise, a new deterministic wideband nonuniform ML DOA estimator is derived and two associated processing algorithms are proposed. The first algorithm is based on an iterative procedure which stepwise concentrates the log-likelihood function with respect to the DOAs and the noise nuisance parameters, while the second is a noniterative algorithm that maximizes the derived approximately concentrated log-likelihood function. The performance of the proposed algorithms is tested through extensive computer simulations. Simulation results show the stepwise-concentrated ML algorithm (SC-ML requires only a few iterations to converge and both the SC-ML and the approximately-concentrated ML algorithm (AC-ML attain a solution close to the derived CRB at high signal-to-noise ratio.
L.U.St: a tool for approximated maximum likelihood supertree reconstruction.
Akanni, Wasiu A; Creevey, Christopher J; Wilkinson, Mark; Pisani, Davide
2014-06-12
Supertrees combine disparate, partially overlapping trees to generate a synthesis that provides a high level perspective that cannot be attained from the inspection of individual phylogenies. Supertrees can be seen as meta-analytical tools that can be used to make inferences based on results of previous scientific studies. Their meta-analytical application has increased in popularity since it was realised that the power of statistical tests for the study of evolutionary trends critically depends on the use of taxon-dense phylogenies. Further to that, supertrees have found applications in phylogenomics where they are used to combine gene trees and recover species phylogenies based on genome-scale data sets. Here, we present the L.U.St package, a python tool for approximate maximum likelihood supertree inference and illustrate its application using a genomic data set for the placental mammals. L.U.St allows the calculation of the approximate likelihood of a supertree, given a set of input trees, performs heuristic searches to look for the supertree of highest likelihood, and performs statistical tests of two or more supertrees. To this end, L.U.St implements a winning sites test allowing ranking of a collection of a-priori selected hypotheses, given as a collection of input supertree topologies. It also outputs a file of input-tree-wise likelihood scores that can be used as input to CONSEL for calculation of standard tests of two trees (e.g. Kishino-Hasegawa, Shimidoara-Hasegawa and Approximately Unbiased tests). This is the first fully parametric implementation of a supertree method, it has clearly understood properties, and provides several advantages over currently available supertree approaches. It is easy to implement and works on any platform that has python installed. bitBucket page - https://afro-juju@bitbucket.org/afro-juju/l.u.st.git. Davide.Pisani@bristol.ac.uk.
Maximum-likelihood fitting of data dominated by Poisson statistical uncertainties
International Nuclear Information System (INIS)
Stoneking, M.R.; Den Hartog, D.J.
1996-06-01
The fitting of data by χ 2 -minimization is valid only when the uncertainties in the data are normally distributed. When analyzing spectroscopic or particle counting data at very low signal level (e.g., a Thomson scattering diagnostic), the uncertainties are distributed with a Poisson distribution. The authors have developed a maximum-likelihood method for fitting data that correctly treats the Poisson statistical character of the uncertainties. This method maximizes the total probability that the observed data are drawn from the assumed fit function using the Poisson probability function to determine the probability for each data point. The algorithm also returns uncertainty estimates for the fit parameters. They compare this method with a χ 2 -minimization routine applied to both simulated and real data. Differences in the returned fits are greater at low signal level (less than ∼20 counts per measurement). the maximum-likelihood method is found to be more accurate and robust, returning a narrower distribution of values for the fit parameters with fewer outliers
Maximum likelihood-based analysis of photon arrival trajectories in single-molecule FRET
Energy Technology Data Exchange (ETDEWEB)
Waligorska, Marta [Adam Mickiewicz University, Faculty of Chemistry, Grunwaldzka 6, 60-780 Poznan (Poland); Molski, Andrzej, E-mail: amolski@amu.edu.pl [Adam Mickiewicz University, Faculty of Chemistry, Grunwaldzka 6, 60-780 Poznan (Poland)
2012-07-25
Highlights: Black-Right-Pointing-Pointer We study model selection and parameter recovery from single-molecule FRET experiments. Black-Right-Pointing-Pointer We examine the maximum likelihood-based analysis of two-color photon trajectories. Black-Right-Pointing-Pointer The number of observed photons determines the performance of the method. Black-Right-Pointing-Pointer For long trajectories, one can extract mean dwell times that are comparable to inter-photon times. -- Abstract: When two fluorophores (donor and acceptor) are attached to an immobilized biomolecule, anti-correlated fluctuations of the donor and acceptor fluorescence caused by Foerster resonance energy transfer (FRET) report on the conformational kinetics of the molecule. Here we assess the maximum likelihood-based analysis of donor and acceptor photon arrival trajectories as a method for extracting the conformational kinetics. Using computer generated data we quantify the accuracy and precision of parameter estimates and the efficiency of the Akaike information criterion (AIC) and the Bayesian information criterion (BIC) in selecting the true kinetic model. We find that the number of observed photons is the key parameter determining parameter estimation and model selection. For long trajectories, one can extract mean dwell times that are comparable to inter-photon times.
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Hassibi Babak
2002-01-01
Full Text Available Multiple antenna systems are capable of providing high data rate transmissions over wireless channels. When the channels are dispersive, the signal at each receive antenna is a combination of both the current and past symbols sent from all transmit antennas corrupted by noise. The optimal receiver is a maximum-likelihood sequence detector and is often considered to be practically infeasible due to high computational complexity (exponential in number of antennas and channel memory. Therefore, in practice, one often settles for a less complex suboptimal receiver structure, typically with an equalizer meant to suppress both the intersymbol and interuser interference, followed by the decoder. We propose a sphere decoding for the sequence detection in multiple antenna communication systems over dispersive channels. The sphere decoding provides the maximum-likelihood estimate with computational complexity comparable to the standard space-time decision-feedback equalizing (DFE algorithms. The performance and complexity of the sphere decoding are compared with the DFE algorithm by means of simulations.
Maximum-likelihood methods for array processing based on time-frequency distributions
Zhang, Yimin; Mu, Weifeng; Amin, Moeness G.
1999-11-01
This paper proposes a novel time-frequency maximum likelihood (t-f ML) method for direction-of-arrival (DOA) estimation for non- stationary signals, and compares this method with conventional maximum likelihood DOA estimation techniques. Time-frequency distributions localize the signal power in the time-frequency domain, and as such enhance the effective SNR, leading to improved DOA estimation. The localization of signals with different t-f signatures permits the division of the time-frequency domain into smaller regions, each contains fewer signals than those incident on the array. The reduction of the number of signals within different time-frequency regions not only reduces the required number of sensors, but also decreases the computational load in multi- dimensional optimizations. Compared to the recently proposed time- frequency MUSIC (t-f MUSIC), the proposed t-f ML method can be applied in coherent environments, without the need to perform any type of preprocessing that is subject to both array geometry and array aperture.
Accuracy of maximum likelihood estimates of a two-state model in single-molecule FRET
Energy Technology Data Exchange (ETDEWEB)
Gopich, Irina V. [Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland 20892 (United States)
2015-01-21
Photon sequences from single-molecule Förster resonance energy transfer (FRET) experiments can be analyzed using a maximum likelihood method. Parameters of the underlying kinetic model (FRET efficiencies of the states and transition rates between conformational states) are obtained by maximizing the appropriate likelihood function. In addition, the errors (uncertainties) of the extracted parameters can be obtained from the curvature of the likelihood function at the maximum. We study the standard deviations of the parameters of a two-state model obtained from photon sequences with recorded colors and arrival times. The standard deviations can be obtained analytically in a special case when the FRET efficiencies of the states are 0 and 1 and in the limiting cases of fast and slow conformational dynamics. These results are compared with the results of numerical simulations. The accuracy and, therefore, the ability to predict model parameters depend on how fast the transition rates are compared to the photon count rate. In the limit of slow transitions, the key parameters that determine the accuracy are the number of transitions between the states and the number of independent photon sequences. In the fast transition limit, the accuracy is determined by the small fraction of photons that are correlated with their neighbors. The relative standard deviation of the relaxation rate has a “chevron” shape as a function of the transition rate in the log-log scale. The location of the minimum of this function dramatically depends on how well the FRET efficiencies of the states are separated.
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Zhang Zhang
2009-06-01
Full Text Available A major analytical challenge in computational biology is the detection and description of clusters of specified site types, such as polymorphic or substituted sites within DNA or protein sequences. Progress has been stymied by a lack of suitable methods to detect clusters and to estimate the extent of clustering in discrete linear sequences, particularly when there is no a priori specification of cluster size or cluster count. Here we derive and demonstrate a maximum likelihood method of hierarchical clustering. Our method incorporates a tripartite divide-and-conquer strategy that models sequence heterogeneity, delineates clusters, and yields a profile of the level of clustering associated with each site. The clustering model may be evaluated via model selection using the Akaike Information Criterion, the corrected Akaike Information Criterion, and the Bayesian Information Criterion. Furthermore, model averaging using weighted model likelihoods may be applied to incorporate model uncertainty into the profile of heterogeneity across sites. We evaluated our method by examining its performance on a number of simulated datasets as well as on empirical polymorphism data from diverse natural alleles of the Drosophila alcohol dehydrogenase gene. Our method yielded greater power for the detection of clustered sites across a breadth of parameter ranges, and achieved better accuracy and precision of estimation of clusters, than did the existing empirical cumulative distribution function statistics.
MAXIMUM LIKELIHOOD CLASSIFICATION OF HIGH-RESOLUTION SAR IMAGES IN URBAN AREA
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M. Soheili Majd
2012-09-01
Full Text Available In this work, we propose a state-of-the-art on statistical analysis of polarimetric synthetic aperture radar (SAR data, through the modeling of several indices. We concentrate on eight ground classes which have been carried out from amplitudes, co-polarisation ratio, depolarization ratios, and other polarimetric descriptors. To study their different statistical behaviours, we consider Gauss, log- normal, Beta I, Weibull, Gamma, and Fisher statistical models and estimate their parameters using three methods: method of moments (MoM, maximum-likelihood (ML methodology, and log-cumulants method (MoML. Then, we study the opportunity of introducing this information in an adapted supervised classification scheme based on Maximum–Likelihood and Fisher pdf. Our work relies on an image of a suburban area, acquired by the airborne RAMSES SAR sensor of ONERA. The results prove the potential of such data to discriminate urban surfaces and show the usefulness of adapting any classical classification algorithm however classification maps present a persistant class confusion between flat gravelled or concrete roofs and trees.
Maximum likelihood fitting of FROC curves under an initial-detection-and-candidate-analysis model
International Nuclear Information System (INIS)
Edwards, Darrin C.; Kupinski, Matthew A.; Metz, Charles E.; Nishikawa, Robert M.
2002-01-01
We have developed a model for FROC curve fitting that relates the observer's FROC performance not to the ROC performance that would be obtained if the observer's responses were scored on a per image basis, but rather to a hypothesized ROC performance that the observer would obtain in the task of classifying a set of 'candidate detections' as positive or negative. We adopt the assumptions of the Bunch FROC model, namely that the observer's detections are all mutually independent, as well as assumptions qualitatively similar to, but different in nature from, those made by Chakraborty in his AFROC scoring methodology. Under the assumptions of our model, we show that the observer's FROC performance is a linearly scaled version of the candidate analysis ROC curve, where the scaling factors are just given by the FROC operating point coordinates for detecting initial candidates. Further, we show that the likelihood function of the model parameters given observational data takes on a simple form, and we develop a maximum likelihood method for fitting a FROC curve to this data. FROC and AFROC curves are produced for computer vision observer datasets and compared with the results of the AFROC scoring method. Although developed primarily with computer vision schemes in mind, we hope that the methodology presented here will prove worthy of further study in other applications as well
Neandertal admixture in Eurasia confirmed by maximum-likelihood analysis of three genomes.
Lohse, Konrad; Frantz, Laurent A F
2014-04-01
Although there has been much interest in estimating histories of divergence and admixture from genomic data, it has proved difficult to distinguish recent admixture from long-term structure in the ancestral population. Thus, recent genome-wide analyses based on summary statistics have sparked controversy about the possibility of interbreeding between Neandertals and modern humans in Eurasia. Here we derive the probability of full mutational configurations in nonrecombining sequence blocks under both admixture and ancestral structure scenarios. Dividing the genome into short blocks gives an efficient way to compute maximum-likelihood estimates of parameters. We apply this likelihood scheme to triplets of human and Neandertal genomes and compare the relative support for a model of admixture from Neandertals into Eurasian populations after their expansion out of Africa against a history of persistent structure in their common ancestral population in Africa. Our analysis allows us to conclusively reject a model of ancestral structure in Africa and instead reveals strong support for Neandertal admixture in Eurasia at a higher rate (3.4-7.3%) than suggested previously. Using analysis and simulations we show that our inference is more powerful than previous summary statistics and robust to realistic levels of recombination.
Frequency-Domain Maximum-Likelihood Estimation of High-Voltage Pulse Transformer Model Parameters
Aguglia, D; Martins, C.D.A.
2014-01-01
This paper presents an offline frequency-domain nonlinear and stochastic identification method for equivalent model parameter estimation of high-voltage pulse transformers. Such kinds of transformers are widely used in the pulsed-power domain, and the difficulty in deriving pulsed-power converter optimal control strategies is directly linked to the accuracy of the equivalent circuit parameters. These components require models which take into account electric fields energies represented by stray capacitance in the equivalent circuit. These capacitive elements must be accurately identified, since they greatly influence the general converter performances. A nonlinear frequency-based identification method, based on maximum-likelihood estimation, is presented, and a sensitivity analysis of the best experimental test to be considered is carried out. The procedure takes into account magnetic saturation and skin effects occurring in the windings during the frequency tests. The presented method is validated by experim...
Directory of Open Access Journals (Sweden)
López-Valcarce Roberto
2004-01-01
Full Text Available We address the problem of estimating the speed of a road vehicle from its acoustic signature, recorded by a pair of omnidirectional microphones located next to the road. This choice of sensors is motivated by their nonintrusive nature as well as low installation and maintenance costs. A novel estimation technique is proposed, which is based on the maximum likelihood principle. It directly estimates car speed without any assumptions on the acoustic signal emitted by the vehicle. This has the advantages of bypassing troublesome intermediate delay estimation steps as well as eliminating the need for an accurate yet general enough acoustic traffic model. An analysis of the estimate for narrowband and broadband sources is provided and verified with computer simulations. The estimation algorithm uses a bank of modified crosscorrelators and therefore it is well suited to DSP implementation, performing well with preliminary field data.
A Sum-of-Squares and Semidefinite Programming Approach for Maximum Likelihood DOA Estimation
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Shu Cai
2016-12-01
Full Text Available Direction of arrival (DOA estimation using a uniform linear array (ULA is a classical problem in array signal processing. In this paper, we focus on DOA estimation based on the maximum likelihood (ML criterion, transform the estimation problem into a novel formulation, named as sum-of-squares (SOS, and then solve it using semidefinite programming (SDP. We first derive the SOS and SDP method for DOA estimation in the scenario of a single source and then extend it under the framework of alternating projection for multiple DOA estimation. The simulations demonstrate that the SOS- and SDP-based algorithms can provide stable and accurate DOA estimation when the number of snapshots is small and the signal-to-noise ratio (SNR is low. Moveover, it has a higher spatial resolution compared to existing methods based on the ML criterion.
Kojima, Yohei; Takeda, Kazuaki; Adachi, Fumiyuki
Frequency-domain equalization (FDE) based on the minimum mean square error (MMSE) criterion can provide better downlink bit error rate (BER) performance of direct sequence code division multiple access (DS-CDMA) than the conventional rake combining in a frequency-selective fading channel. FDE requires accurate channel estimation. In this paper, we propose a new 2-step maximum likelihood channel estimation (MLCE) for DS-CDMA with FDE in a very slow frequency-selective fading environment. The 1st step uses the conventional pilot-assisted MMSE-CE and the 2nd step carries out the MLCE using decision feedback from the 1st step. The BER performance improvement achieved by 2-step MLCE over pilot assisted MMSE-CE is confirmed by computer simulation.
Dermoune, Azzouz; Simon, Eric Pierre
2017-12-01
This paper is a theoretical analysis of the maximum likelihood (ML) channel estimator for orthogonal frequency-division multiplexing (OFDM) systems in the presence of unknown interference. The following theoretical results are presented. Firstly, the uniqueness of the ML solution for practical applications, i.e., when thermal noise is present, is analytically demonstrated when the number of transmitted OFDM symbols is strictly greater than one. The ML solution is then derived from the iterative conditional ML (CML) algorithm. Secondly, it is shown that the channel estimate can be described as an algebraic function whose inputs are the initial value and the means and variances of the received samples. Thirdly, it is theoretically demonstrated that the channel estimator is not biased. The second and the third results are obtained by employing oblique projection theory. Furthermore, these results are confirmed by numerical results.
Maximum Likelihood PSD Estimation for Speech Enhancement in Reverberation and Noise
DEFF Research Database (Denmark)
Kuklasinski, Adam; Doclo, Simon; Jensen, Søren Holdt
2016-01-01
In this contribution we focus on the problem of power spectral density (PSD) estimation from multiple microphone signals in reverberant and noisy environments. The PSD estimation method proposed in this paper is based on the maximum likelihood (ML) methodology. In particular, we derive a novel ML...... instrumental measures and is shown to be higher than when the competing estimator is used. Moreover, we perform a speech intelligibility test where we demonstrate that both the proposed and the competing PSD estimators lead to similar intelligibility improvements......., it is shown numerically that the mean squared estimation error achieved by the proposed method is near the limit set by the corresponding Cram´er-Rao lower bound. The speech dereverberation performance of a multi-channel Wiener filter (MWF) based on the proposed PSD estimators is measured using several...
A new maximum likelihood blood velocity estimator incorporating spatial and temporal correlation
DEFF Research Database (Denmark)
Schlaikjer, Malene; Jensen, Jørgen Arendt
2001-01-01
and space. This paper presents a new estimator (STC-MLE), which incorporates the correlation property. It is an expansion of the maximum likelihood estimator (MLE) developed by Ferrara et al. With the MLE a cross-correlation analysis between consecutive RF-lines on complex form is carried out for a range...... of possible velocities. In the new estimator an additional similarity investigation for each evaluated velocity and the available velocity estimates in a temporal (between frames) and spatial (within frames) neighborhood is performed. An a priori probability density term in the distribution...... of the observations gives a probability measure of the correlation between the velocities. Both the MLE and the STC-MLE have been evaluated on simulated and in-vivo RF-data obtained from the carotid artery. Using the MLE 4.1% of the estimates deviate significantly from the true velocities, when the performance...
Smolin, John A; Gambetta, Jay M; Smith, Graeme
2012-02-17
We provide an efficient method for computing the maximum-likelihood mixed quantum state (with density matrix ρ) given a set of measurement outcomes in a complete orthonormal operator basis subject to Gaussian noise. Our method works by first changing basis yielding a candidate density matrix μ which may have nonphysical (negative) eigenvalues, and then finding the nearest physical state under the 2-norm. Our algorithm takes at worst O(d(4)) for the basis change plus O(d(3)) for finding ρ where d is the dimension of the quantum state. In the special case where the measurement basis is strings of Pauli operators, the basis change takes only O(d(3)) as well. The workhorse of the algorithm is a new linear-time method for finding the closest probability distribution (in Euclidean distance) to a set of real numbers summing to one.
Maximum Likelihood-Based Methods for Target Velocity Estimation with Distributed MIMO Radar
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Zhenxin Cao
2018-02-01
Full Text Available The estimation problem for target velocity is addressed in this in the scenario with a distributed multi-input multi-out (MIMO radar system. A maximum likelihood (ML-based estimation method is derived with the knowledge of target position. Then, in the scenario without the knowledge of target position, an iterative method is proposed to estimate the target velocity by updating the position information iteratively. Moreover, the Carmér-Rao Lower Bounds (CRLBs for both scenarios are derived, and the performance degradation of velocity estimation without the position information is also expressed. Simulation results show that the proposed estimation methods can approach the CRLBs, and the velocity estimation performance can be further improved by increasing either the number of radar antennas or the information accuracy of the target position. Furthermore, compared with the existing methods, a better estimation performance can be achieved.
On Maximum Likelihood Estimation for Left Censored Burr Type III Distribution
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Navid Feroze
2015-12-01
Full Text Available Burr type III is an important distribution used to model the failure time data. The paper addresses the problem of estimation of parameters of the Burr type III distribution based on maximum likelihood estimation (MLE when the samples are left censored. As the closed form expression for the MLEs of the parameters cannot be derived, the approximate solutions have been obtained through iterative procedures. An extensive simulation study has been carried out to investigate the performance of the estimators with respect to sample size, censoring rate and true parametric values. A real life example has also been presented. The study revealed that the proposed estimators are consistent and capable of providing efficient results under small to moderate samples.
Implementation of non-linear filters for iterative penalized maximum likelihood image reconstruction
International Nuclear Information System (INIS)
Liang, Z.; Gilland, D.; Jaszczak, R.; Coleman, R.
1990-01-01
In this paper, the authors report on the implementation of six edge-preserving, noise-smoothing, non-linear filters applied in image space for iterative penalized maximum-likelihood (ML) SPECT image reconstruction. The non-linear smoothing filters implemented were the median filter, the E 6 filter, the sigma filter, the edge-line filter, the gradient-inverse filter, and the 3-point edge filter with gradient-inverse filter, and the 3-point edge filter with gradient-inverse weight. A 3 x 3 window was used for all these filters. The best image obtained, by viewing the profiles through the image in terms of noise-smoothing, edge-sharpening, and contrast, was the one smoothed with the 3-point edge filter. The computation time for the smoothing was less than 1% of one iteration, and the memory space for the smoothing was negligible. These images were compared with the results obtained using Bayesian analysis
Targeted search for continuous gravitational waves: Bayesian versus maximum-likelihood statistics
International Nuclear Information System (INIS)
Prix, Reinhard; Krishnan, Badri
2009-01-01
We investigate the Bayesian framework for detection of continuous gravitational waves (GWs) in the context of targeted searches, where the phase evolution of the GW signal is assumed to be known, while the four amplitude parameters are unknown. We show that the orthodox maximum-likelihood statistic (known as F-statistic) can be rediscovered as a Bayes factor with an unphysical prior in amplitude parameter space. We introduce an alternative detection statistic ('B-statistic') using the Bayes factor with a more natural amplitude prior, namely an isotropic probability distribution for the orientation of GW sources. Monte Carlo simulations of targeted searches show that the resulting Bayesian B-statistic is more powerful in the Neyman-Pearson sense (i.e., has a higher expected detection probability at equal false-alarm probability) than the frequentist F-statistic.
Pritikin, Joshua N; Brick, Timothy R; Neale, Michael C
2018-04-01
A novel method for the maximum likelihood estimation of structural equation models (SEM) with both ordinal and continuous indicators is introduced using a flexible multivariate probit model for the ordinal indicators. A full information approach ensures unbiased estimates for data missing at random. Exceeding the capability of prior methods, up to 13 ordinal variables can be included before integration time increases beyond 1 s per row. The method relies on the axiom of conditional probability to split apart the distribution of continuous and ordinal variables. Due to the symmetry of the axiom, two similar methods are available. A simulation study provides evidence that the two similar approaches offer equal accuracy. A further simulation is used to develop a heuristic to automatically select the most computationally efficient approach. Joint ordinal continuous SEM is implemented in OpenMx, free and open-source software.
DEFF Research Database (Denmark)
Cherchi, Elisabetta; Guevara, Cristian
2012-01-01
with cross-sectional or with panel data, and (d) EM systematically attained more efficient estimators than the MSL method. The results imply that if the purpose of the estimation is only to determine the ratios of the model parameters (e.g., the value of time), the EM method should be preferred. For all......The random coefficients logit model allows a more realistic representation of agents' behavior. However, the estimation of that model may involve simulation, which may become impractical with many random coefficients because of the curse of dimensionality. In this paper, the traditional maximum...... simulated likelihood (MSL) method is compared with the alternative expectation- maximization (EM) method, which does not require simulation. Previous literature had shown that for cross-sectional data, MSL outperforms the EM method in the ability to recover the true parameters and estimation time...
Li, Xinya; Deng, Z. Daniel; Sun, Yannan; Martinez, Jayson J.; Fu, Tao; McMichael, Geoffrey A.; Carlson, Thomas J.
2014-11-01
Better understanding of fish behavior is vital for recovery of many endangered species including salmon. The Juvenile Salmon Acoustic Telemetry System (JSATS) was developed to observe the out-migratory behavior of juvenile salmonids tagged by surgical implantation of acoustic micro-transmitters and to estimate the survival when passing through dams on the Snake and Columbia Rivers. A robust three-dimensional solver was needed to accurately and efficiently estimate the time sequence of locations of fish tagged with JSATS acoustic transmitters, to describe in sufficient detail the information needed to assess the function of dam-passage design alternatives. An approximate maximum likelihood solver was developed using measurements of time difference of arrival from all hydrophones in receiving arrays on which a transmission was detected. Field experiments demonstrated that the developed solver performed significantly better in tracking efficiency and accuracy than other solvers described in the literature.
BOREAS TE-18 Landsat TM Maximum Likelihood Classification Image of the NSA
Hall, Forrest G. (Editor); Knapp, David
2000-01-01
The BOREAS TE-18 team focused its efforts on using remotely sensed data to characterize the successional and disturbance dynamics of the boreal forest for use in carbon modeling. The objective of this classification is to provide the BOREAS investigators with a data product that characterizes the land cover of the NSA. A Landsat-5 TM image from 20-Aug-1988 was used to derive this classification. A standard supervised maximum likelihood classification approach was used to produce this classification. The data are provided in a binary image format file. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Activity Archive Center (DAAC).
MADmap: A Massively Parallel Maximum-Likelihood Cosmic Microwave Background Map-Maker
Energy Technology Data Exchange (ETDEWEB)
Cantalupo, Christopher; Borrill, Julian; Jaffe, Andrew; Kisner, Theodore; Stompor, Radoslaw
2009-06-09
MADmap is a software application used to produce maximum-likelihood images of the sky from time-ordered data which include correlated noise, such as those gathered by Cosmic Microwave Background (CMB) experiments. It works efficiently on platforms ranging from small workstations to the most massively parallel supercomputers. Map-making is a critical step in the analysis of all CMB data sets, and the maximum-likelihood approach is the most accurate and widely applicable algorithm; however, it is a computationally challenging task. This challenge will only increase with the next generation of ground-based, balloon-borne and satellite CMB polarization experiments. The faintness of the B-mode signal that these experiments seek to measure requires them to gather enormous data sets. MADmap is already being run on up to O(1011) time samples, O(108) pixels and O(104) cores, with ongoing work to scale to the next generation of data sets and supercomputers. We describe MADmap's algorithm based around a preconditioned conjugate gradient solver, fast Fourier transforms and sparse matrix operations. We highlight MADmap's ability to address problems typically encountered in the analysis of realistic CMB data sets and describe its application to simulations of the Planck and EBEX experiments. The massively parallel and distributed implementation is detailed and scaling complexities are given for the resources required. MADmap is capable of analysing the largest data sets now being collected on computing resources currently available, and we argue that, given Moore's Law, MADmap will be capable of reducing the most massive projected data sets.
Supervised maximum-likelihood weighting of composite protein networks for complex prediction
Directory of Open Access Journals (Sweden)
Yong Chern Han
2012-12-01
Full Text Available Abstract Background Protein complexes participate in many important cellular functions, so finding the set of existent complexes is essential for understanding the organization and regulation of processes in the cell. With the availability of large amounts of high-throughput protein-protein interaction (PPI data, many algorithms have been proposed to discover protein complexes from PPI networks. However, such approaches are hindered by the high rate of noise in high-throughput PPI data, including spurious and missing interactions. Furthermore, many transient interactions are detected between proteins that are not from the same complex, while not all proteins from the same complex may actually interact. As a result, predicted complexes often do not match true complexes well, and many true complexes go undetected. Results We address these challenges by integrating PPI data with other heterogeneous data sources to construct a composite protein network, and using a supervised maximum-likelihood approach to weight each edge based on its posterior probability of belonging to a complex. We then use six different clustering algorithms, and an aggregative clustering strategy, to discover complexes in the weighted network. We test our method on Saccharomyces cerevisiae and Homo sapiens, and show that complex discovery is improved: compared to previously proposed supervised and unsupervised weighting approaches, our method recalls more known complexes, achieves higher precision at all recall levels, and generates novel complexes of greater functional similarity. Furthermore, our maximum-likelihood approach allows learned parameters to be used to visualize and evaluate the evidence of novel predictions, aiding human judgment of their credibility. Conclusions Our approach integrates multiple data sources with supervised learning to create a weighted composite protein network, and uses six clustering algorithms with an aggregative clustering strategy to
Joint maximum-likelihood magnitudes of presumed underground nuclear test explosions
Peacock, Sheila; Douglas, Alan; Bowers, David
2017-08-01
Body-wave magnitudes (mb) of 606 seismic disturbances caused by presumed underground nuclear test explosions at specific test sites between 1964 and 1996 have been derived from station amplitudes collected by the International Seismological Centre (ISC), by a joint inversion for mb and station-specific magnitude corrections. A maximum-likelihood method was used to reduce the upward bias of network mean magnitudes caused by data censoring, where arrivals at stations that do not report arrivals are assumed to be hidden by the ambient noise at the time. Threshold noise levels at each station were derived from the ISC amplitudes using the method of Kelly and Lacoss, which fits to the observed magnitude-frequency distribution a Gutenberg-Richter exponential decay truncated at low magnitudes by an error function representing the low-magnitude threshold of the station. The joint maximum-likelihood inversion is applied to arrivals from the sites: Semipalatinsk (Kazakhstan) and Novaya Zemlya, former Soviet Union; Singer (Lop Nor), China; Mururoa and Fangataufa, French Polynesia; and Nevada, USA. At sites where eight or more arrivals could be used to derive magnitudes and station terms for 25 or more explosions (Nevada, Semipalatinsk and Mururoa), the resulting magnitudes and station terms were fixed and a second inversion carried out to derive magnitudes for additional explosions with three or more arrivals. 93 more magnitudes were thus derived. During processing for station thresholds, many stations were rejected for sparsity of data, obvious errors in reported amplitude, or great departure of the reported amplitude-frequency distribution from the expected left-truncated exponential decay. Abrupt changes in monthly mean amplitude at a station apparently coincide with changes in recording equipment and/or analysis method at the station.
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César da Silva Chagas
2013-04-01
Full Text Available Soil surveys are the main source of spatial information on soils and have a range of different applications, mainly in agriculture. The continuity of this activity has however been severely compromised, mainly due to a lack of governmental funding. The purpose of this study was to evaluate the feasibility of two different classifiers (artificial neural networks and a maximum likelihood algorithm in the prediction of soil classes in the northwest of the state of Rio de Janeiro. Terrain attributes such as elevation, slope, aspect, plan curvature and compound topographic index (CTI and indices of clay minerals, iron oxide and Normalized Difference Vegetation Index (NDVI, derived from Landsat 7 ETM+ sensor imagery, were used as discriminating variables. The two classifiers were trained and validated for each soil class using 300 and 150 samples respectively, representing the characteristics of these classes in terms of the discriminating variables. According to the statistical tests, the accuracy of the classifier based on artificial neural networks (ANNs was greater than of the classic Maximum Likelihood Classifier (MLC. Comparing the results with 126 points of reference showed that the resulting ANN map (73.81 % was superior to the MLC map (57.94 %. The main errors when using the two classifiers were caused by: a the geological heterogeneity of the area coupled with problems related to the geological map; b the depth of lithic contact and/or rock exposure, and c problems with the environmental correlation model used due to the polygenetic nature of the soils. This study confirms that the use of terrain attributes together with remote sensing data by an ANN approach can be a tool to facilitate soil mapping in Brazil, primarily due to the availability of low-cost remote sensing data and the ease by which terrain attributes can be obtained.
Castrillon, Julio; Genton, Marc G.; Yokota, Rio
2015-01-01
We develop a multi-level restricted Gaussian maximum likelihood method for estimating the covariance function parameters and computing the best unbiased predictor. Our approach produces a new set of multi-level contrasts where the deterministic
Model uncertainty estimation and risk assessment is essential to environmental management and informed decision making on pollution mitigation strategies. In this study, we apply a probabilistic methodology, which combines Bayesian Monte Carlo simulation and Maximum Likelihood e...
Godolphin, E. J.
1980-01-01
It is shown that the estimation procedure of Walker leads to estimates of the parameters of a Gaussian moving average process which are asymptotically equivalent to the maximum likelihood estimates proposed by Whittle and represented by Godolphin.
FPGA Hardware Acceleration of a Phylogenetic Tree Reconstruction with Maximum Parsimony Algorithm
BLOCK, Henry; MARUYAMA, Tsutomu
2017-01-01
In this paper, we present an FPGA hardware implementation for a phylogenetic tree reconstruction with a maximum parsimony algorithm. We base our approach on a particular stochastic local search algorithm that uses the Progressive Neighborhood and the Indirect Calculation of Tree Lengths method. This method is widely used for the acceleration of the phylogenetic tree reconstruction algorithm in software. In our implementation, we define a tree structure and accelerate the search by parallel an...
DEFF Research Database (Denmark)
Boiroux, Dimitri; Juhl, Rune; Madsen, Henrik
2016-01-01
This paper addresses maximum likelihood parameter estimation of continuous-time nonlinear systems with discrete-time measurements. We derive an efficient algorithm for the computation of the log-likelihood function and its gradient, which can be used in gradient-based optimization algorithms....... This algorithm uses UD decomposition of symmetric matrices and the array algorithm for covariance update and gradient computation. We test our algorithm on the Lotka-Volterra equations. Compared to the maximum likelihood estimation based on finite difference gradient computation, we get a significant speedup...
THE GENERALIZED MAXIMUM LIKELIHOOD METHOD APPLIED TO HIGH PRESSURE PHASE EQUILIBRIUM
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Lúcio CARDOZO-FILHO
1997-12-01
Full Text Available The generalized maximum likelihood method was used to determine binary interaction parameters between carbon dioxide and components of orange essential oil. Vapor-liquid equilibrium was modeled with Peng-Robinson and Soave-Redlich-Kwong equations, using a methodology proposed in 1979 by Asselineau, Bogdanic and Vidal. Experimental vapor-liquid equilibrium data on binary mixtures formed with carbon dioxide and compounds usually found in orange essential oil were used to test the model. These systems were chosen to demonstrate that the maximum likelihood method produces binary interaction parameters for cubic equations of state capable of satisfactorily describing phase equilibrium, even for a binary such as ethanol/CO2. Results corroborate that the Peng-Robinson, as well as the Soave-Redlich-Kwong, equation can be used to describe phase equilibrium for the following systems: components of essential oil of orange/CO2.Foi empregado o método da máxima verossimilhança generalizado para determinação de parâmetros de interação binária entre os componentes do óleo essencial de laranja e dióxido de carbono. Foram usados dados experimentais de equilíbrio líquido-vapor de misturas binárias de dióxido de carbono e componentes do óleo essencial de laranja. O equilíbrio líquido-vapor foi modelado com as equações de Peng-Robinson e de Soave-Redlich-Kwong usando a metodologia proposta em 1979 por Asselineau, Bogdanic e Vidal. A escolha destes sistemas teve como objetivo demonstrar que o método da máxima verosimilhança produz parâmetros de interação binária, para equações cúbicas de estado capazes de descrever satisfatoriamente até mesmo o equilíbrio para o binário etanol/CO2. Os resultados comprovam que tanto a equação de Peng-Robinson quanto a de Soave-Redlich-Kwong podem ser empregadas para descrever o equilíbrio de fases para o sistemas: componentes do óleo essencial de laranja/CO2.
Wobbling and LSF-based maximum likelihood expectation maximization reconstruction for wobbling PET
International Nuclear Information System (INIS)
Kim, Hang-Keun; Son, Young-Don; Kwon, Dae-Hyuk; Joo, Yohan; Cho, Zang-Hee
2016-01-01
Positron emission tomography (PET) is a widely used imaging modality; however, the PET spatial resolution is not yet satisfactory for precise anatomical localization of molecular activities. Detector size is the most important factor because it determines the intrinsic resolution, which is approximately half of the detector size and determines the ultimate PET resolution. Detector size, however, cannot be made too small because both the decreased detection efficiency and the increased septal penetration effect degrade the image quality. A wobbling and line spread function (LSF)-based maximum likelihood expectation maximization (WL-MLEM) algorithm, which combined the MLEM iterative reconstruction algorithm with wobbled sampling and LSF-based deconvolution using the system matrix, was proposed for improving the spatial resolution of PET without reducing the scintillator or detector size. The new algorithm was evaluated using a simulation, and its performance was compared with that of the existing algorithms, such as conventional MLEM and LSF-based MLEM. Simulations demonstrated that the WL-MLEM algorithm yielded higher spatial resolution and image quality than the existing algorithms. The WL-MLEM algorithm with wobbling PET yielded substantially improved resolution compared with conventional algorithms with stationary PET. The algorithm can be easily extended to other iterative reconstruction algorithms, such as maximum a priori (MAP) and ordered subset expectation maximization (OSEM). The WL-MLEM algorithm with wobbling PET may offer improvements in both sensitivity and resolution, the two most sought-after features in PET design. - Highlights: • This paper proposed WL-MLEM algorithm for PET and demonstrated its performance. • WL-MLEM algorithm effectively combined wobbling and line spread function based MLEM. • WL-MLEM provided improvements in the spatial resolution and the PET image quality. • WL-MLEM can be easily extended to the other iterative
Stability of maximum-likelihood-based clustering methods: exploring the backbone of classifications
International Nuclear Information System (INIS)
Mungan, Muhittin; Ramasco, José J
2010-01-01
Components of complex systems are often classified according to the way they interact with each other. In graph theory such groups are known as clusters or communities. Many different techniques have been recently proposed to detect them, some of which involve inference methods using either Bayesian or maximum likelihood approaches. In this paper, we study a statistical model designed for detecting clusters based on connection similarity. The basic assumption of the model is that the graph was generated by a certain grouping of the nodes and an expectation maximization algorithm is employed to infer that grouping. We show that the method admits further development to yield a stability analysis of the groupings that quantifies the extent to which each node influences its neighbors' group membership. Our approach naturally allows for the identification of the key elements responsible for the grouping and their resilience to changes in the network. Given the generality of the assumptions underlying the statistical model, such nodes are likely to play special roles in the original system. We illustrate this point by analyzing several empirical networks for which further information about the properties of the nodes is available. The search and identification of stabilizing nodes constitutes thus a novel technique to characterize the relevance of nodes in complex networks
Bias correction for estimated QTL effects using the penalized maximum likelihood method.
Zhang, J; Yue, C; Zhang, Y-M
2012-04-01
A penalized maximum likelihood method has been proposed as an important approach to the detection of epistatic quantitative trait loci (QTL). However, this approach is not optimal in two special situations: (1) closely linked QTL with effects in opposite directions and (2) small-effect QTL, because the method produces downwardly biased estimates of QTL effects. The present study aims to correct the bias by using correction coefficients and shifting from the use of a uniform prior on the variance parameter of a QTL effect to that of a scaled inverse chi-square prior. The results of Monte Carlo simulation experiments show that the improved method increases the power from 25 to 88% in the detection of two closely linked QTL of equal size in opposite directions and from 60 to 80% in the identification of QTL with small effects (0.5% of the total phenotypic variance). We used the improved method to detect QTL responsible for the barley kernel weight trait using 145 doubled haploid lines developed in the North American Barley Genome Mapping Project. Application of the proposed method to other shrinkage estimation of QTL effects is discussed.
Tsou, Haiping; Yan, Tsun-Yee
1999-04-01
This paper describes an extended-source spatial acquisition and tracking scheme for planetary optical communications. This scheme uses the Sun-lit Earth image as the beacon signal, which can be computed according to the current Sun-Earth-Probe angle from a pre-stored Earth image or a received snapshot taken by other Earth-orbiting satellite. Onboard the spacecraft, the reference image is correlated in the transform domain with the received image obtained from a detector array, which is assumed to have each of its pixels corrupted by an independent additive white Gaussian noise. The coordinate of the ground station is acquired and tracked, respectively, by an open-loop acquisition algorithm and a closed-loop tracking algorithm derived from the maximum likelihood criterion. As shown in the paper, the optimal spatial acquisition requires solving two nonlinear equations, or iteratively solving their linearized variants, to estimate the coordinate when translation in the relative positions of onboard and ground transceivers is considered. Similar assumption of linearization leads to the closed-loop spatial tracking algorithm in which the loop feedback signals can be derived from the weighted transform-domain correlation. Numerical results using a sample Sun-lit Earth image demonstrate that sub-pixel resolutions can be achieved by this scheme in a high disturbance environment.
International Nuclear Information System (INIS)
Vanhaelewyn, G.; Callens, F.; Gruen, R.
2000-01-01
In order to determine the components which give rise to the EPR spectrum around g = 2 we have applied Maximum Likelihood Common Factor Analysis (MLCFA) on the EPR spectra of enamel sample 1126 which has previously been analysed by continuous wave and pulsed EPR as well as EPR microscopy. MLCFA yielded agreeing results on three sets of X-band spectra and the following components were identified: an orthorhombic component attributed to CO - 2 , an axial component CO 3- 3 , as well as four isotropic components, three of which could be attributed to SO - 2 , a tumbling CO - 2 and a central line of a dimethyl radical. The X-band results were confirmed by analysis of Q-band spectra where three additional isotropic lines were found, however, these three components could not be attributed to known radicals. The orthorhombic component was used to establish dose response curves for the assessment of the past radiation dose, D E . The results appear to be more reliable than those based on conventional peak-to-peak EPR intensity measurements or simple Gaussian deconvolution methods
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Dansereau Richard M
2007-01-01
Full Text Available We present a new technique for separating two speech signals from a single recording. The proposed method bridges the gap between underdetermined blind source separation techniques and those techniques that model the human auditory system, that is, computational auditory scene analysis (CASA. For this purpose, we decompose the speech signal into the excitation signal and the vocal-tract-related filter and then estimate the components from the mixed speech using a hybrid model. We first express the probability density function (PDF of the mixed speech's log spectral vectors in terms of the PDFs of the underlying speech signal's vocal-tract-related filters. Then, the mean vectors of PDFs of the vocal-tract-related filters are obtained using a maximum likelihood estimator given the mixed signal. Finally, the estimated vocal-tract-related filters along with the extracted fundamental frequencies are used to reconstruct estimates of the individual speech signals. The proposed technique effectively adds vocal-tract-related filter characteristics as a new cue to CASA models using a new grouping technique based on an underdetermined blind source separation. We compare our model with both an underdetermined blind source separation and a CASA method. The experimental results show that our model outperforms both techniques in terms of SNR improvement and the percentage of crosstalk suppression.
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Mohammad H. Radfar
2006-11-01
Full Text Available We present a new technique for separating two speech signals from a single recording. The proposed method bridges the gap between underdetermined blind source separation techniques and those techniques that model the human auditory system, that is, computational auditory scene analysis (CASA. For this purpose, we decompose the speech signal into the excitation signal and the vocal-tract-related filter and then estimate the components from the mixed speech using a hybrid model. We first express the probability density function (PDF of the mixed speech's log spectral vectors in terms of the PDFs of the underlying speech signal's vocal-tract-related filters. Then, the mean vectors of PDFs of the vocal-tract-related filters are obtained using a maximum likelihood estimator given the mixed signal. Finally, the estimated vocal-tract-related filters along with the extracted fundamental frequencies are used to reconstruct estimates of the individual speech signals. The proposed technique effectively adds vocal-tract-related filter characteristics as a new cue to CASA models using a new grouping technique based on an underdetermined blind source separation. We compare our model with both an underdetermined blind source separation and a CASA method. The experimental results show that our model outperforms both techniques in terms of SNR improvement and the percentage of crosstalk suppression.
Efficient Levenberg-Marquardt minimization of the maximum likelihood estimator for Poisson deviates
International Nuclear Information System (INIS)
Laurence, T.; Chromy, B.
2010-01-01
Histograms of counted events are Poisson distributed, but are typically fitted without justification using nonlinear least squares fitting. The more appropriate maximum likelihood estimator (MLE) for Poisson distributed data is seldom used. We extend the use of the Levenberg-Marquardt algorithm commonly used for nonlinear least squares minimization for use with the MLE for Poisson distributed data. In so doing, we remove any excuse for not using this more appropriate MLE. We demonstrate the use of the algorithm and the superior performance of the MLE using simulations and experiments in the context of fluorescence lifetime imaging. Scientists commonly form histograms of counted events from their data, and extract parameters by fitting to a specified model. Assuming that the probability of occurrence for each bin is small, event counts in the histogram bins will be distributed according to the Poisson distribution. We develop here an efficient algorithm for fitting event counting histograms using the maximum likelihood estimator (MLE) for Poisson distributed data, rather than the non-linear least squares measure. This algorithm is a simple extension of the common Levenberg-Marquardt (L-M) algorithm, is simple to implement, quick and robust. Fitting using a least squares measure is most common, but it is the maximum likelihood estimator only for Gaussian-distributed data. Non-linear least squares methods may be applied to event counting histograms in cases where the number of events is very large, so that the Poisson distribution is well approximated by a Gaussian. However, it is not easy to satisfy this criterion in practice - which requires a large number of events. It has been well-known for years that least squares procedures lead to biased results when applied to Poisson-distributed data; a recent paper providing extensive characterization of these biases in exponential fitting is given. The more appropriate measure based on the maximum likelihood estimator (MLE
Penalized maximum-likelihood sinogram restoration for dual focal spot computed tomography
International Nuclear Information System (INIS)
Forthmann, P; Koehler, T; Begemann, P G C; Defrise, M
2007-01-01
Due to various system non-idealities, the raw data generated by a computed tomography (CT) machine are not readily usable for reconstruction. Although the deterministic nature of corruption effects such as crosstalk and afterglow permits correction by deconvolution, there is a drawback because deconvolution usually amplifies noise. Methods that perform raw data correction combined with noise suppression are commonly termed sinogram restoration methods. The need for sinogram restoration arises, for example, when photon counts are low and non-statistical reconstruction algorithms such as filtered backprojection are used. Many modern CT machines offer a dual focal spot (DFS) mode, which serves the goal of increased radial sampling by alternating the focal spot between two positions on the anode plate during the scan. Although the focal spot mode does not play a role with respect to how the data are affected by the above-mentioned corruption effects, it needs to be taken into account if regularized sinogram restoration is to be applied to the data. This work points out the subtle difference in processing that sinogram restoration for DFS requires, how it is correctly employed within the penalized maximum-likelihood sinogram restoration algorithm and what impact it has on image quality
Maximum Likelihood Time-of-Arrival Estimation of Optical Pulses via Photon-Counting Photodetectors
Erkmen, Baris I.; Moision, Bruce E.
2010-01-01
Many optical imaging, ranging, and communications systems rely on the estimation of the arrival time of an optical pulse. Recently, such systems have been increasingly employing photon-counting photodetector technology, which changes the statistics of the observed photocurrent. This requires time-of-arrival estimators to be developed and their performances characterized. The statistics of the output of an ideal photodetector, which are well modeled as a Poisson point process, were considered. An analytical model was developed for the mean-square error of the maximum likelihood (ML) estimator, demonstrating two phenomena that cause deviations from the minimum achievable error at low signal power. An approximation was derived to the threshold at which the ML estimator essentially fails to provide better than a random guess of the pulse arrival time. Comparing the analytic model performance predictions to those obtained via simulations, it was verified that the model accurately predicts the ML performance over all regimes considered. There is little prior art that attempts to understand the fundamental limitations to time-of-arrival estimation from Poisson statistics. This work establishes both a simple mathematical description of the error behavior, and the associated physical processes that yield this behavior. Previous work on mean-square error characterization for ML estimators has predominantly focused on additive Gaussian noise. This work demonstrates that the discrete nature of the Poisson noise process leads to a distinctly different error behavior.
Maximum likelihood-based analysis of single-molecule photon arrival trajectories
Hajdziona, Marta; Molski, Andrzej
2011-02-01
In this work we explore the statistical properties of the maximum likelihood-based analysis of one-color photon arrival trajectories. This approach does not involve binning and, therefore, all of the information contained in an observed photon strajectory is used. We study the accuracy and precision of parameter estimates and the efficiency of the Akaike information criterion and the Bayesian information criterion (BIC) in selecting the true kinetic model. We focus on the low excitation regime where photon trajectories can be modeled as realizations of Markov modulated Poisson processes. The number of observed photons is the key parameter in determining model selection and parameter estimation. For example, the BIC can select the true three-state model from competing two-, three-, and four-state kinetic models even for relatively short trajectories made up of 2 × 103 photons. When the intensity levels are well-separated and 104 photons are observed, the two-state model parameters can be estimated with about 10% precision and those for a three-state model with about 20% precision.
Maximum likelihood-based analysis of single-molecule photon arrival trajectories.
Hajdziona, Marta; Molski, Andrzej
2011-02-07
In this work we explore the statistical properties of the maximum likelihood-based analysis of one-color photon arrival trajectories. This approach does not involve binning and, therefore, all of the information contained in an observed photon strajectory is used. We study the accuracy and precision of parameter estimates and the efficiency of the Akaike information criterion and the Bayesian information criterion (BIC) in selecting the true kinetic model. We focus on the low excitation regime where photon trajectories can be modeled as realizations of Markov modulated Poisson processes. The number of observed photons is the key parameter in determining model selection and parameter estimation. For example, the BIC can select the true three-state model from competing two-, three-, and four-state kinetic models even for relatively short trajectories made up of 2 × 10(3) photons. When the intensity levels are well-separated and 10(4) photons are observed, the two-state model parameters can be estimated with about 10% precision and those for a three-state model with about 20% precision.
Implementation of linear filters for iterative penalized maximum likelihood SPECT reconstruction
International Nuclear Information System (INIS)
Liang, Z.
1991-01-01
This paper reports on six low-pass linear filters applied in frequency space implemented for iterative penalized maximum-likelihood (ML) SPECT image reconstruction. The filters implemented were the Shepp-Logan filter, the Butterworth filer, the Gaussian filter, the Hann filter, the Parzen filer, and the Lagrange filter. The low-pass filtering was applied in frequency space to projection data for the initial estimate and to the difference of projection data and reprojected data for higher order approximations. The projection data were acquired experimentally from a chest phantom consisting of non-uniform attenuating media. All the filters could effectively remove the noise and edge artifacts associated with ML approach if the frequency cutoff was properly chosen. The improved performance of the Parzen and Lagrange filters relative to the others was observed. The best image, by viewing its profiles in terms of noise-smoothing, edge-sharpening, and contrast, was the one obtained with the Parzen filter. However, the Lagrange filter has the potential to consider the characteristics of detector response function
Statistical analysis of maximum likelihood estimator images of human brain FDG PET studies
International Nuclear Information System (INIS)
Llacer, J.; Veklerov, E.; Hoffman, E.J.; Nunez, J.; Coakley, K.J.
1993-01-01
The work presented in this paper evaluates the statistical characteristics of regional bias and expected error in reconstructions of real PET data of human brain fluorodeoxiglucose (FDG) studies carried out by the maximum likelihood estimator (MLE) method with a robust stopping rule, and compares them with the results of filtered backprojection (FBP) reconstructions and with the method of sieves. The task that the authors have investigated is that of quantifying radioisotope uptake in regions-of-interest (ROI's). They first describe a robust methodology for the use of the MLE method with clinical data which contains only one adjustable parameter: the kernel size for a Gaussian filtering operation that determines final resolution and expected regional error. Simulation results are used to establish the fundamental characteristics of the reconstructions obtained by out methodology, corresponding to the case in which the transition matrix is perfectly known. Then, data from 72 independent human brain FDG scans from four patients are used to show that the results obtained from real data are consistent with the simulation, although the quality of the data and of the transition matrix have an effect on the final outcome
Fast Maximum-Likelihood Decoder for Quasi-Orthogonal Space-Time Block Code
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Adel Ahmadi
2015-01-01
Full Text Available Motivated by the decompositions of sphere and QR-based methods, in this paper we present an extremely fast maximum-likelihood (ML detection approach for quasi-orthogonal space-time block code (QOSTBC. The proposed algorithm with a relatively simple design exploits structure of quadrature amplitude modulation (QAM constellations to achieve its goal and can be extended to any arbitrary constellation. Our decoder utilizes a new decomposition technique for ML metric which divides the metric into independent positive parts and a positive interference part. Search spaces of symbols are substantially reduced by employing the independent parts and statistics of noise. Symbols within the search spaces are successively evaluated until the metric is minimized. Simulation results confirm that the proposed decoder’s performance is superior to many of the recently published state-of-the-art solutions in terms of complexity level. More specifically, it was possible to verify that application of the new algorithms with 1024-QAM would decrease the computational complexity compared to state-of-the-art solution with 16-QAM.
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Sonali Sachin Sankpal
2016-01-01
Full Text Available Scattering and absorption of light is main reason for limited visibility in water. The suspended particles and dissolved chemical compounds in water are also responsible for scattering and absorption of light in water. The limited visibility in water results in degradation of underwater images. The visibility can be increased by using artificial light source in underwater imaging system. But the artificial light illuminates the scene in a nonuniform fashion. It produces bright spot at the center with the dark region at surroundings. In some cases imaging system itself creates dark region in the image by producing shadow on the objects. The problem of nonuniform illumination is neglected by the researchers in most of the image enhancement techniques of underwater images. Also very few methods are discussed showing the results on color images. This paper suggests a method for nonuniform illumination correction for underwater images. The method assumes that natural underwater images are Rayleigh distributed. This paper used maximum likelihood estimation of scale parameter to map distribution of image to Rayleigh distribution. The method is compared with traditional methods for nonuniform illumination correction using no-reference image quality metrics like average luminance, average information entropy, normalized neighborhood function, average contrast, and comprehensive assessment function.
Chernick, Julian A.; Perlovsky, Leonid I.; Tye, David M.
1994-06-01
This paper describes applications of maximum likelihood adaptive neural system (MLANS) to the characterization of clutter in IR images and to the identification of targets. The characterization of image clutter is needed to improve target detection and to enhance the ability to compare performance of different algorithms using diverse imagery data. Enhanced unambiguous IFF is important for fratricide reduction while automatic cueing and targeting is becoming an ever increasing part of operations. We utilized MLANS which is a parametric neural network that combines optimal statistical techniques with a model-based approach. This paper shows that MLANS outperforms classical classifiers, the quadratic classifier and the nearest neighbor classifier, because on the one hand it is not limited to the usual Gaussian distribution assumption and can adapt in real time to the image clutter distribution; on the other hand MLANS learns from fewer samples and is more robust than the nearest neighbor classifiers. Future research will address uncooperative IFF using fused IR and MMW data.
Maximum likelihood estimation of semiparametric mixture component models for competing risks data.
Choi, Sangbum; Huang, Xuelin
2014-09-01
In the analysis of competing risks data, the cumulative incidence function is a useful quantity to characterize the crude risk of failure from a specific event type. In this article, we consider an efficient semiparametric analysis of mixture component models on cumulative incidence functions. Under the proposed mixture model, latency survival regressions given the event type are performed through a class of semiparametric models that encompasses the proportional hazards model and the proportional odds model, allowing for time-dependent covariates. The marginal proportions of the occurrences of cause-specific events are assessed by a multinomial logistic model. Our mixture modeling approach is advantageous in that it makes a joint estimation of model parameters associated with all competing risks under consideration, satisfying the constraint that the cumulative probability of failing from any cause adds up to one given any covariates. We develop a novel maximum likelihood scheme based on semiparametric regression analysis that facilitates efficient and reliable estimation. Statistical inferences can be conveniently made from the inverse of the observed information matrix. We establish the consistency and asymptotic normality of the proposed estimators. We validate small sample properties with simulations and demonstrate the methodology with a data set from a study of follicular lymphoma. © 2014, The International Biometric Society.
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Andrey eStepanyuk
2014-10-01
Full Text Available Dendritic integration and neuronal firing patterns strongly depend on biophysical properties of synaptic ligand-gated channels. However, precise estimation of biophysical parameters of these channels in their intrinsic environment is complicated and still unresolved problem. Here we describe a novel method based on a maximum likelihood approach that allows to estimate not only the unitary current of synaptic receptor channels but also their multiple conductance levels, kinetic constants, the number of receptors bound with a neurotransmitter and the peak open probability from experimentally feasible number of postsynaptic currents. The new method also improves the accuracy of evaluation of unitary current as compared to the peak-scaled non-stationary fluctuation analysis, leading to a possibility to precisely estimate this important parameter from a few postsynaptic currents recorded in steady-state conditions. Estimation of unitary current with this method is robust even if postsynaptic currents are generated by receptors having different kinetic parameters, the case when peak-scaled non-stationary fluctuation analysis is not applicable. Thus, with the new method, routinely recorded postsynaptic currents could be used to study the properties of synaptic receptors in their native biochemical environment.
International Nuclear Information System (INIS)
Rajan, Jeny; Jeurissen, Ben; Sijbers, Jan; Verhoye, Marleen; Van Audekerke, Johan
2011-01-01
In this paper, we propose a method to denoise magnitude magnetic resonance (MR) images, which are Rician distributed. Conventionally, maximum likelihood methods incorporate the Rice distribution to estimate the true, underlying signal from a local neighborhood within which the signal is assumed to be constant. However, if this assumption is not met, such filtering will lead to blurred edges and loss of fine structures. As a solution to this problem, we put forward the concept of restricted local neighborhoods where the true intensity for each noisy pixel is estimated from a set of preselected neighboring pixels. To this end, a reference image is created from the noisy image using a recently proposed nonlocal means algorithm. This reference image is used as a prior for further noise reduction. A scheme is developed to locally select an appropriate subset of pixels from which the underlying signal is estimated. Experimental results based on the peak signal to noise ratio, structural similarity index matrix, Bhattacharyya coefficient and mean absolute difference from synthetic and real MR images demonstrate the superior performance of the proposed method over other state-of-the-art methods.
Extended maximum likelihood analysis of apparent flattenings of S0 and spiral galaxies
International Nuclear Information System (INIS)
Okamura, Sadanori; Takase, Bunshiro; Hamabe, Masaru; Nakada, Yoshikazu; Kodaira, Keiichi.
1981-01-01
Apparent flattenings of S0 and spiral galaxies compiled by Sandage et al. (1970) and van den Bergh (1977), and those listed in the Second Reference Catalogue (RC2) are analyzed by means of the extended maximum likelihood method which was recently developed in the information theory for statistical model identification. Emphasis is put on the possible difference in the distribution of intrinsic flattenings between S0's and spirals as a group, and on the apparent disagreements present in the previous results. The present analysis shows that (1) One cannot conclude on the basis of the data in the Reference Catalogue of Bright Galaxies (RCBG) that the distribution of intrinsic flattenings of spirals is almost identical to that of S0's; spirals have wider dispersion than S0's, and there are more round systems in spirals than in S0's. (2) The distribution of intrinsic flattenings of S0's and spirals derived from the data in RC2 again indicates a significant difference from each other. (3) The distribution of intrinsic flattenings of S0's exhibits different characteristics depending upon the surface-brightness level; the distribution with one component is obtained from the data at RCBG level (--23.5 mag arcsec -2 ) and that with two components at RC2 level (25 mag arcsec -2 ). (author)
Analysis of Pairwise Interactions in a Maximum Likelihood Sense to Identify Leaders in a Group
Directory of Open Access Journals (Sweden)
Violet Mwaffo
2017-07-01
Full Text Available Collective motion in animal groups manifests itself in the form of highly coordinated maneuvers determined by local interactions among individuals. A particularly critical question in understanding the mechanisms behind such interactions is to detect and classify leader–follower relationships within the group. In the technical literature of coupled dynamical systems, several methods have been proposed to reconstruct interaction networks, including linear correlation analysis, transfer entropy, and event synchronization. While these analyses have been helpful in reconstructing network models from neuroscience to public health, rules on the most appropriate method to use for a specific dataset are lacking. Here, we demonstrate the possibility of detecting leaders in a group from raw positional data in a model-free approach that combines multiple methods in a maximum likelihood sense. We test our framework on synthetic data of groups of self-propelled Vicsek particles, where a single agent acts as a leader and both the size of the interaction region and the level of inherent noise are systematically varied. To assess the feasibility of detecting leaders in real-world applications, we study a synthetic dataset of fish shoaling, generated by using a recent data-driven model for social behavior, and an experimental dataset of pharmacologically treated zebrafish. Not only does our approach offer a robust strategy to detect leaders in synthetic data but it also allows for exploring the role of psychoactive compounds on leader–follower relationships.
Ellis, Sam; Reader, Andrew J
2018-04-26
Many clinical contexts require the acquisition of multiple positron emission tomography (PET) scans of a single subject, for example to observe and quantify changes in functional behaviour in tumours after treatment in oncology. Typically, the datasets from each of these scans are reconstructed individually, without exploiting the similarities between them. We have recently shown that sharing information between longitudinal PET datasets by penalising voxel-wise differences during image reconstruction can improve reconstructed images by reducing background noise and increasing the contrast-to-noise ratio of high activity lesions. Here we present two additional novel longitudinal difference-image priors and evaluate their performance using 2D simulation studies and a 3D real dataset case study. We have previously proposed a simultaneous difference-image-based penalised maximum likelihood (PML) longitudinal image reconstruction method that encourages sparse difference images (DS-PML), and in this work we propose two further novel prior terms. The priors are designed to encourage longitudinal images with corresponding differences which have i) low entropy (DE-PML), and ii) high sparsity in their spatial gradients (DTV-PML). These two new priors and the originally proposed longitudinal prior were applied to 2D simulated treatment response [ 18 F]fluorodeoxyglucose (FDG) brain tumour datasets and compared to standard maximum likelihood expectation-maximisation (MLEM) reconstructions. These 2D simulation studies explored the effects of penalty strengths, tumour behaviour, and inter-scan coupling on reconstructed images. Finally, a real two-scan longitudinal data series acquired from a head and neck cancer patient was reconstructed with the proposed methods and the results compared to standard reconstruction methods. Using any of the three priors with an appropriate penalty strength produced images with noise levels equivalent to those seen when using standard
Deconvolving the wedge: maximum-likelihood power spectra via spherical-wave visibility modelling
Ghosh, A.; Mertens, F. G.; Koopmans, L. V. E.
2018-03-01
Direct detection of the Epoch of Reionization (EoR) via the red-shifted 21-cm line will have unprecedented implications on the study of structure formation in the infant Universe. To fulfil this promise, current and future 21-cm experiments need to detect this weak EoR signal in the presence of foregrounds that are several orders of magnitude larger. This requires extreme noise control and improved wide-field high dynamic-range imaging techniques. We propose a new imaging method based on a maximum likelihood framework which solves for the interferometric equation directly on the sphere, or equivalently in the uvw-domain. The method uses the one-to-one relation between spherical waves and spherical harmonics (SpH). It consistently handles signals from the entire sky, and does not require a w-term correction. The SpH coefficients represent the sky-brightness distribution and the visibilities in the uvw-domain, and provide a direct estimate of the spatial power spectrum. Using these spectrally smooth SpH coefficients, bright foregrounds can be removed from the signal, including their side-lobe noise, which is one of the limiting factors in high dynamics-range wide-field imaging. Chromatic effects causing the so-called `wedge' are effectively eliminated (i.e. deconvolved) in the cylindrical (k⊥, k∥) power spectrum, compared to a power spectrum computed directly from the images of the foreground visibilities where the wedge is clearly present. We illustrate our method using simulated Low-Frequency Array observations, finding an excellent reconstruction of the input EoR signal with minimal bias.
Penalized maximum likelihood reconstruction for x-ray differential phase-contrast tomography
International Nuclear Information System (INIS)
Brendel, Bernhard; Teuffenbach, Maximilian von; Noël, Peter B.; Pfeiffer, Franz; Koehler, Thomas
2016-01-01
Purpose: The purpose of this work is to propose a cost function with regularization to iteratively reconstruct attenuation, phase, and scatter images simultaneously from differential phase contrast (DPC) acquisitions, without the need of phase retrieval, and examine its properties. Furthermore this reconstruction method is applied to an acquisition pattern that is suitable for a DPC tomographic system with continuously rotating gantry (sliding window acquisition), overcoming the severe smearing in noniterative reconstruction. Methods: We derive a penalized maximum likelihood reconstruction algorithm to directly reconstruct attenuation, phase, and scatter image from the measured detector values of a DPC acquisition. The proposed penalty comprises, for each of the three images, an independent smoothing prior. Image quality of the proposed reconstruction is compared to images generated with FBP and iterative reconstruction after phase retrieval. Furthermore, the influence between the priors is analyzed. Finally, the proposed reconstruction algorithm is applied to experimental sliding window data acquired at a synchrotron and results are compared to reconstructions based on phase retrieval. Results: The results show that the proposed algorithm significantly increases image quality in comparison to reconstructions based on phase retrieval. No significant mutual influence between the proposed independent priors could be observed. Further it could be illustrated that the iterative reconstruction of a sliding window acquisition results in images with substantially reduced smearing artifacts. Conclusions: Although the proposed cost function is inherently nonconvex, it can be used to reconstruct images with less aliasing artifacts and less streak artifacts than reconstruction methods based on phase retrieval. Furthermore, the proposed method can be used to reconstruct images of sliding window acquisitions with negligible smearing artifacts
Improved efficiency of maximum likelihood analysis of time series with temporally correlated errors
Langbein, John
2017-08-01
Most time series of geophysical phenomena have temporally correlated errors. From these measurements, various parameters are estimated. For instance, from geodetic measurements of positions, the rates and changes in rates are often estimated and are used to model tectonic processes. Along with the estimates of the size of the parameters, the error in these parameters needs to be assessed. If temporal correlations are not taken into account, or each observation is assumed to be independent, it is likely that any estimate of the error of these parameters will be too low and the estimated value of the parameter will be biased. Inclusion of better estimates of uncertainties is limited by several factors, including selection of the correct model for the background noise and the computational requirements to estimate the parameters of the selected noise model for cases where there are numerous observations. Here, I address the second problem of computational efficiency using maximum likelihood estimates (MLE). Most geophysical time series have background noise processes that can be represented as a combination of white and power-law noise, 1/f^{α } with frequency, f. With missing data, standard spectral techniques involving FFTs are not appropriate. Instead, time domain techniques involving construction and inversion of large data covariance matrices are employed. Bos et al. (J Geod, 2013. doi: 10.1007/s00190-012-0605-0) demonstrate one technique that substantially increases the efficiency of the MLE methods, yet is only an approximate solution for power-law indices >1.0 since they require the data covariance matrix to be Toeplitz. That restriction can be removed by simply forming a data filter that adds noise processes rather than combining them in quadrature. Consequently, the inversion of the data covariance matrix is simplified yet provides robust results for a wider range of power-law indices.
FlowMax: A Computational Tool for Maximum Likelihood Deconvolution of CFSE Time Courses.
Directory of Open Access Journals (Sweden)
Maxim Nikolaievich Shokhirev
Full Text Available The immune response is a concerted dynamic multi-cellular process. Upon infection, the dynamics of lymphocyte populations are an aggregate of molecular processes that determine the activation, division, and longevity of individual cells. The timing of these single-cell processes is remarkably widely distributed with some cells undergoing their third division while others undergo their first. High cell-to-cell variability and technical noise pose challenges for interpreting popular dye-dilution experiments objectively. It remains an unresolved challenge to avoid under- or over-interpretation of such data when phenotyping gene-targeted mouse models or patient samples. Here we develop and characterize a computational methodology to parameterize a cell population model in the context of noisy dye-dilution data. To enable objective interpretation of model fits, our method estimates fit sensitivity and redundancy by stochastically sampling the solution landscape, calculating parameter sensitivities, and clustering to determine the maximum-likelihood solution ranges. Our methodology accounts for both technical and biological variability by using a cell fluorescence model as an adaptor during population model fitting, resulting in improved fit accuracy without the need for ad hoc objective functions. We have incorporated our methodology into an integrated phenotyping tool, FlowMax, and used it to analyze B cells from two NFκB knockout mice with distinct phenotypes; we not only confirm previously published findings at a fraction of the expended effort and cost, but reveal a novel phenotype of nfkb1/p105/50 in limiting the proliferative capacity of B cells following B-cell receptor stimulation. In addition to complementing experimental work, FlowMax is suitable for high throughput analysis of dye dilution studies within clinical and pharmacological screens with objective and quantitative conclusions.
International Nuclear Information System (INIS)
Stsepankou, D; Arns, A; Hesser, J; Ng, S K; Zygmanski, P
2012-01-01
The objective of this paper is to evaluate an iterative maximum likelihood (ML) cone–beam computed tomography (CBCT) reconstruction with total variation (TV) regularization with respect to the robustness of the algorithm due to data inconsistencies. Three different and (for clinical application) typical classes of errors are considered for simulated phantom and measured projection data: quantum noise, defect detector pixels and projection matrix errors. To quantify those errors we apply error measures like mean square error, signal-to-noise ratio, contrast-to-noise ratio and streak indicator. These measures are derived from linear signal theory and generalized and applied for nonlinear signal reconstruction. For quality check, we focus on resolution and CT-number linearity based on a Catphan phantom. All comparisons are made versus the clinical standard, the filtered backprojection algorithm (FBP). In our results, we confirm and substantially extend previous results on iterative reconstruction such as massive undersampling of the number of projections. Errors of projection matrix parameters of up to 1° projection angle deviations are still in the tolerance level. Single defect pixels exhibit ring artifacts for each method. However using defect pixel compensation, allows up to 40% of defect pixels for passing the standard clinical quality check. Further, the iterative algorithm is extraordinarily robust in the low photon regime (down to 0.05 mAs) when compared to FPB, allowing for extremely low-dose image acquisitions, a substantial issue when considering daily CBCT imaging for position correction in radiotherapy. We conclude that the ML method studied herein is robust under clinical quality assurance conditions. Consequently, low-dose regime imaging, especially for daily patient localization in radiation therapy is possible without change of the current hardware of the imaging system. (paper)
Weigmann, U; Petersen, J
1996-08-01
Visual acuity determination according to DIN 58,220 does not make full use of the information received about the patient, in contrast to the staircase method. Thus, testing the same number of optotypes, the staircase method should yield more reproducible acuity results. On the other hand, the staircase method gives systematically higher acuity values because it converges on the 48% point of the psychometric function (for Landolt rings in eight positions) and not on the 65% probability, as DIN 58,220 with criterion 3/5 does. This bias can be avoided by means of a modified evaluation. Using the staircase data we performed a maximum likelihood estimate of the psychometric function as a whole and computed the acuity value for 65% probability of correct answers. We determined monocular visual acuity in 102 persons with widely differing visual performance. Each subject underwent four tests in random order, two according to DIN 58,220 and two using the modified staircase method (Landolt rings in eight positions scaled by a factor 1.26; PC monitor with 1024 x 768 pixels; distance 4.5 m). Each test was performed with 25 optotypes. The two procedures provide the same mean visual acuity values (difference less than 0.02 acuity steps). The test-retest results match in 30.4% of DIN repetitions but in 50% of the staircases. The standard deviation of the test-retest difference is 1.41 (DIN) and 1.06 (modified staircase) acuity steps. Thus the standard deviation of the single test is 1.0 (DIN) and 0.75 (modified staircase) acuity steps. The new method provides visual acuity values identical to DIN 58,220 but is superior with respect to reproducibility.
Parameter-free bearing fault detection based on maximum likelihood estimation and differentiation
International Nuclear Information System (INIS)
Bozchalooi, I Soltani; Liang, Ming
2009-01-01
Bearing faults can lead to malfunction and ultimately complete stall of many machines. The conventional high-frequency resonance (HFR) method has been commonly used for bearing fault detection. However, it is often very difficult to obtain and calibrate bandpass filter parameters, i.e. the center frequency and bandwidth, the key to the success of the HFR method. This inevitably undermines the usefulness of the conventional HFR technique. To avoid such difficulties, we propose parameter-free, versatile yet straightforward techniques to detect bearing faults. We focus on two types of measured signals frequently encountered in practice: (1) a mixture of impulsive faulty bearing vibrations and intrinsic background noise and (2) impulsive faulty bearing vibrations blended with intrinsic background noise and vibration interferences. To design a proper signal processing technique for each case, we analyze the effects of intrinsic background noise and vibration interferences on amplitude demodulation. For the first case, a maximum likelihood-based fault detection method is proposed to accommodate the Rician distribution of the amplitude-demodulated signal mixture. For the second case, we first illustrate that the high-amplitude low-frequency vibration interferences can make the amplitude demodulation ineffective. Then we propose a differentiation method to enhance the fault detectability. It is shown that the iterative application of a differentiation step can boost the relative strength of the impulsive faulty bearing signal component with respect to the vibration interferences. This preserves the effectiveness of amplitude demodulation and hence leads to more accurate fault detection. The proposed approaches are evaluated on simulated signals and experimental data acquired from faulty bearings
International Nuclear Information System (INIS)
Song, N; Frey, E C; He, B; Wahl, R L
2011-01-01
Optimizing targeted radionuclide therapy requires patient-specific estimation of organ doses. The organ doses are estimated from quantitative nuclear medicine imaging studies, many of which involve planar whole body scans. We have previously developed the quantitative planar (QPlanar) processing method and demonstrated its ability to provide more accurate activity estimates than conventional geometric-mean-based planar (CPlanar) processing methods using physical phantom and simulation studies. The QPlanar method uses the maximum likelihood-expectation maximization algorithm, 3D organ volume of interests (VOIs), and rigorous models of physical image degrading factors to estimate organ activities. However, the QPlanar method requires alignment between the 3D organ VOIs and the 2D planar projections and assumes uniform activity distribution in each VOI. This makes application to patients challenging. As a result, in this paper we propose an extended QPlanar (EQPlanar) method that provides independent-organ rigid registration and includes multiple background regions. We have validated this method using both Monte Carlo simulation and patient data. In the simulation study, we evaluated the precision and accuracy of the method in comparison to the original QPlanar method. For the patient studies, we compared organ activity estimates at 24 h after injection with those from conventional geometric mean-based planar quantification using a 24 h post-injection quantitative SPECT reconstruction as the gold standard. We also compared the goodness of fit of the measured and estimated projections obtained from the EQPlanar method to those from the original method at four other time points where gold standard data were not available. In the simulation study, more accurate activity estimates were provided by the EQPlanar method for all the organs at all the time points compared with the QPlanar method. Based on the patient data, we concluded that the EQPlanar method provided a
Kelderman, Henk
1991-01-01
In this paper, algorithms are described for obtaining the maximum likelihood estimates of the parameters in log-linear models. Modified versions of the iterative proportional fitting and Newton-Raphson algorithms are described that work on the minimal sufficient statistics rather than on the usual
Kelderman, Henk
1992-01-01
In this paper algorithms are described for obtaining the maximum likelihood estimates of the parameters in loglinear models. Modified versions of the iterative proportional fitting and Newton-Raphson algorithms are described that work on the minimal sufficient statistics rather than on the usual
Kieftenbeld, Vincent; Natesan, Prathiba
2012-01-01
Markov chain Monte Carlo (MCMC) methods enable a fully Bayesian approach to parameter estimation of item response models. In this simulation study, the authors compared the recovery of graded response model parameters using marginal maximum likelihood (MML) and Gibbs sampling (MCMC) under various latent trait distributions, test lengths, and…
Beauducel, Andre; Herzberg, Philipp Yorck
2006-01-01
This simulation study compared maximum likelihood (ML) estimation with weighted least squares means and variance adjusted (WLSMV) estimation. The study was based on confirmatory factor analyses with 1, 2, 4, and 8 factors, based on 250, 500, 750, and 1,000 cases, and on 5, 10, 20, and 40 variables with 2, 3, 4, 5, and 6 categories. There was no…
Bergboer, N.H.; Verdult, V.; Verhaegen, M.H.G.
2002-01-01
We present a numerically efficient implementation of the nonlinear least squares and maximum likelihood identification of multivariable linear time-invariant (LTI) state-space models. This implementation is based on a local parameterization of the system and a gradient search in the resulting
Ning, Jing; Chen, Yong; Piao, Jin
2017-07-01
Publication bias occurs when the published research results are systematically unrepresentative of the population of studies that have been conducted, and is a potential threat to meaningful meta-analysis. The Copas selection model provides a flexible framework for correcting estimates and offers considerable insight into the publication bias. However, maximizing the observed likelihood under the Copas selection model is challenging because the observed data contain very little information on the latent variable. In this article, we study a Copas-like selection model and propose an expectation-maximization (EM) algorithm for estimation based on the full likelihood. Empirical simulation studies show that the EM algorithm and its associated inferential procedure performs well and avoids the non-convergence problem when maximizing the observed likelihood. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
International Nuclear Information System (INIS)
Williams, O. R.; Bennett, K.; Much, R.; Schoenfelder, V.; Blom, J. J.; Ryan, J.
1997-01-01
The maximum likelihood-ratio method is frequently used in COMPTEL analysis to determine the significance of a point source at a given location. In this paper we do not consider whether the likelihood-ratio at a particular location indicates a detection, but rather whether distributions of likelihood-ratios derived from many locations depart from that expected for source free data. We have constructed distributions of likelihood-ratios by reading values from standard COMPTEL maximum-likelihood ratio maps at positions corresponding to the locations of different categories of AGN. Distributions derived from the locations of Seyfert galaxies are indistinguishable, according to a Kolmogorov-Smirnov test, from those obtained from ''random'' locations, but differ slightly from those obtained from the locations of flat spectrum radio loud quasars, OVVs, and BL Lac objects. This difference is not due to known COMPTEL sources, since regions near these sources are excluded from the analysis. We suggest that it might arise from a number of sources with fluxes below the COMPTEL detection threshold
Estimation of stochastic frontier models with fixed-effects through Monte Carlo Maximum Likelihood
Emvalomatis, G.; Stefanou, S.E.; Oude Lansink, A.G.J.M.
2011-01-01
Estimation of nonlinear fixed-effects models is plagued by the incidental parameters problem. This paper proposes a procedure for choosing appropriate densities for integrating the incidental parameters from the likelihood function in a general context. The densities are based on priors that are
Peters, B. C., Jr.; Walker, H. F.
1976-01-01
The problem of obtaining numerically maximum likelihood estimates of the parameters for a mixture of normal distributions is addressed. In recent literature, a certain successive approximations procedure, based on the likelihood equations, is shown empirically to be effective in numerically approximating such maximum-likelihood estimates; however, the reliability of this procedure was not established theoretically. Here, a general iterative procedure is introduced, of the generalized steepest-ascent (deflected-gradient) type, which is just the procedure known in the literature when the step-size is taken to be 1. With probability 1 as the sample size grows large, it is shown that this procedure converges locally to the strongly consistent maximum-likelihood estimate whenever the step-size lies between 0 and 2. The step-size which yields optimal local convergence rates for large samples is determined in a sense by the separation of the component normal densities and is bounded below by a number between 1 and 2.
Peters, B. C., Jr.; Walker, H. F.
1978-01-01
This paper addresses the problem of obtaining numerically maximum-likelihood estimates of the parameters for a mixture of normal distributions. In recent literature, a certain successive-approximations procedure, based on the likelihood equations, was shown empirically to be effective in numerically approximating such maximum-likelihood estimates; however, the reliability of this procedure was not established theoretically. Here, we introduce a general iterative procedure, of the generalized steepest-ascent (deflected-gradient) type, which is just the procedure known in the literature when the step-size is taken to be 1. We show that, with probability 1 as the sample size grows large, this procedure converges locally to the strongly consistent maximum-likelihood estimate whenever the step-size lies between 0 and 2. We also show that the step-size which yields optimal local convergence rates for large samples is determined in a sense by the 'separation' of the component normal densities and is bounded below by a number between 1 and 2.
Lirio, R B; Dondériz, I C; Pérez Abalo, M C
1992-08-01
The methodology of Receiver Operating Characteristic curves based on the signal detection model is extended to evaluate the accuracy of two-stage diagnostic strategies. A computer program is developed for the maximum likelihood estimation of parameters that characterize the sensitivity and specificity of two-stage classifiers according to this extended methodology. Its use is briefly illustrated with data collected in a two-stage screening for auditory defects.
International Nuclear Information System (INIS)
Eisler, P.; Youl, S.; Lwin, T.; Nelson, G.
1983-01-01
Simultaneous fitting of peaks and background functions from gamma-ray spectrometry using multichannel pulse height analysis is considered. The specific case of Gaussian peak and exponential background is treated in detail with respect to simultaneous estimation of both functions by using a technique which incorporates maximum likelihood method as well as a graphical method. Theoretical expressions for the standard errors of the estimates are also obtained. The technique is demonstrated for two experimental data sets. (orig.)
International Nuclear Information System (INIS)
Manglos, S.H.
1992-01-01
Transverse image truncation can be a serious problem for human imaging using cone-beam transmission CT (CB-CT) implemented on a conventional rotating gamma camera. This paper presents a reconstruction method to reduce or eliminate the artifacts resulting from the truncation. The method uses a previously published transmission maximum likelihood EM algorithm, adapted to the cone-beam geometry. The reconstruction method is evaluated qualitatively using three human subjects of various dimensions and various degrees of truncation. (author)
Efficient Maximum Likelihood Estimation for Pedigree Data with the Sum-Product Algorithm.
Engelhardt, Alexander; Rieger, Anna; Tresch, Achim; Mansmann, Ulrich
2016-01-01
We analyze data sets consisting of pedigrees with age at onset of colorectal cancer (CRC) as phenotype. The occurrence of familial clusters of CRC suggests the existence of a latent, inheritable risk factor. We aimed to compute the probability of a family possessing this risk factor as well as the hazard rate increase for these risk factor carriers. Due to the inheritability of this risk factor, the estimation necessitates a costly marginalization of the likelihood. We propose an improved EM algorithm by applying factor graphs and the sum-product algorithm in the E-step. This reduces the computational complexity from exponential to linear in the number of family members. Our algorithm is as precise as a direct likelihood maximization in a simulation study and a real family study on CRC risk. For 250 simulated families of size 19 and 21, the runtime of our algorithm is faster by a factor of 4 and 29, respectively. On the largest family (23 members) in the real data, our algorithm is 6 times faster. We introduce a flexible and runtime-efficient tool for statistical inference in biomedical event data with latent variables that opens the door for advanced analyses of pedigree data. © 2017 S. Karger AG, Basel.
DEFF Research Database (Denmark)
Philipsen, Kirsten Riber; Christiansen, Lasse Engbo; Mandsberg, Lotte Frigaard
2008-01-01
with an exponentially decaying function of the time between observations is suggested. A model with a full covariance structure containing OD-dependent variance and an autocorrelation structure is compared to a model with variance only and with no variance or correlation implemented. It is shown that the model...... are used for parameter estimation. The data is log-transformed such that a linear model can be applied. The transformation changes the variance structure, and hence an OD-dependent variance is implemented in the model. The autocorrelation in the data is demonstrated, and a correlation model...... that best describes data is a model taking into account the full covariance structure. An inference study is made in order to determine whether the growth rate of the five bacteria strains is the same. After applying a likelihood-ratio test to models with a full covariance structure, it is concluded...
Inferring phylogenetic networks by the maximum parsimony criterion: a case study.
Jin, Guohua; Nakhleh, Luay; Snir, Sagi; Tuller, Tamir
2007-01-01
Horizontal gene transfer (HGT) may result in genes whose evolutionary histories disagree with each other, as well as with the species tree. In this case, reconciling the species and gene trees results in a network of relationships, known as the "phylogenetic network" of the set of species. A phylogenetic network that incorporates HGT consists of an underlying species tree that captures vertical inheritance and a set of edges which model the "horizontal" transfer of genetic material. In a series of papers, Nakhleh and colleagues have recently formulated a maximum parsimony (MP) criterion for phylogenetic networks, provided an array of computationally efficient algorithms and heuristics for computing it, and demonstrated its plausibility on simulated data. In this article, we study the performance and robustness of this criterion on biological data. Our findings indicate that MP is very promising when its application is extended to the domain of phylogenetic network reconstruction and HGT detection. In all cases we investigated, the MP criterion detected the correct number of HGT events required to map the evolutionary history of a gene data set onto the species phylogeny. Furthermore, our results indicate that the criterion is robust with respect to both incomplete taxon sampling and the use of different site substitution matrices. Finally, our results show that the MP criterion is very promising in detecting HGT in chimeric genes, whose evolutionary histories are a mix of vertical and horizontal evolution. Besides the performance analysis of MP, our findings offer new insights into the evolution of 4 biological data sets and new possible explanations of HGT scenarios in their evolutionary history.
Directory of Open Access Journals (Sweden)
Moliere Nguile-Makao
2015-12-01
Full Text Available The analysis of interaction effects involving genetic variants and environmental exposures on the risk of adverse obstetric and early-life outcomes is generally performed using standard logistic regression in the case-mother and control-mother design. However such an analysis is inefficient because it does not take into account the natural family-based constraints present in the parent-child relationship. Recently, a new approach based on semi-parametric maximum likelihood estimation was proposed. The advantage of this approach is that it takes into account the parental relationship between the mother and her child in estimation. But a package implementing this method has not been widely available. In this paper, we present SPmlficmcm, an R package implementing this new method and we propose an extension of the method to handle missing offspring genotype data by maximum likelihood estimation. Our choice to treat missing data of the offspring genotype was motivated by the fact that in genetic association studies where the genetic data of mother and child are available, there are usually more missing data on the genotype of the offspring than that of the mother. The package builds a non-linear system from the data and solves and computes the estimates from the gradient and the Hessian matrix of the log profile semi-parametric likelihood function. Finally, we analyze a simulated dataset to show the usefulness of the package.
Guindon, Stéphane; Dufayard, Jean-François; Lefort, Vincent; Anisimova, Maria; Hordijk, Wim; Gascuel, Olivier
2010-05-01
PhyML is a phylogeny software based on the maximum-likelihood principle. Early PhyML versions used a fast algorithm performing nearest neighbor interchanges to improve a reasonable starting tree topology. Since the original publication (Guindon S., Gascuel O. 2003. A simple, fast and accurate algorithm to estimate large phylogenies by maximum likelihood. Syst. Biol. 52:696-704), PhyML has been widely used (>2500 citations in ISI Web of Science) because of its simplicity and a fair compromise between accuracy and speed. In the meantime, research around PhyML has continued, and this article describes the new algorithms and methods implemented in the program. First, we introduce a new algorithm to search the tree space with user-defined intensity using subtree pruning and regrafting topological moves. The parsimony criterion is used here to filter out the least promising topology modifications with respect to the likelihood function. The analysis of a large collection of real nucleotide and amino acid data sets of various sizes demonstrates the good performance of this method. Second, we describe a new test to assess the support of the data for internal branches of a phylogeny. This approach extends the recently proposed approximate likelihood-ratio test and relies on a nonparametric, Shimodaira-Hasegawa-like procedure. A detailed analysis of real alignments sheds light on the links between this new approach and the more classical nonparametric bootstrap method. Overall, our tests show that the last version (3.0) of PhyML is fast, accurate, stable, and ready to use. A Web server and binary files are available from http://www.atgc-montpellier.fr/phyml/.
DEFF Research Database (Denmark)
Danieli, Matteo; Forchhammer, Søren; Andersen, Jakob Dahl
2010-01-01
analysis leads to using maximum mutual information (MMI) as optimality criterion and in turn Kullback-Leibler (KL) divergence as distortion measure. Simulations run based on an LTE-like system have proven that VQ can be implemented in a computationally simple way at low rates of 2-3 bits per LLR value......Modern mobile telecommunication systems, such as 3GPP LTE, make use of Hybrid Automatic Repeat reQuest (HARQ) for efficient and reliable communication between base stations and mobile terminals. To this purpose, marginal posterior probabilities of the received bits are stored in the form of log...
Directory of Open Access Journals (Sweden)
L. STRAGEVITCH
1997-03-01
Full Text Available The equations of the method based on the maximum likelihood principle have been rewritten in a suitable generalized form to allow the use of any number of implicit constraints in the determination of model parameters from experimental data and from the associated experimental uncertainties. In addition to the use of any number of constraints, this method also allows data, with different numbers of constraints, to be reduced simultaneously. Application of the method is illustrated in the reduction of liquid-liquid equilibrium data of binary, ternary and quaternary systems simultaneously
DEFF Research Database (Denmark)
De Carvalho, Elisabeth; Omar, Samir; Slock, Dirk
2013-01-01
We analyze two algorithms that have been introduced previously for Deterministic Maximum Likelihood (DML) blind estimation of multiple FIR channels. The first one is a modification of the Iterative Quadratic ML (IQML) algorithm. IQML gives biased estimates of the channel and performs poorly at low...... to the initialization. Its asymptotic performance does not reach the DML performance though. The second strategy, called Pseudo-Quadratic ML (PQML), is naturally denoised. The denoising in PQML is furthermore more efficient than in DIQML: PQML yields the same asymptotic performance as DML, as opposed to DIQML......, but requires a consistent initialization. We furthermore compare DIQML and PQML to the strategy of alternating minimization w.r.t. symbols and channel for solving DML (AQML). An asymptotic performance analysis, a complexity evaluation and simulation results are also presented. The proposed DIQML and PQML...
Galili, Tal; Meilijson, Isaac
2016-01-02
The Rao-Blackwell theorem offers a procedure for converting a crude unbiased estimator of a parameter θ into a "better" one, in fact unique and optimal if the improvement is based on a minimal sufficient statistic that is complete. In contrast, behind every minimal sufficient statistic that is not complete, there is an improvable Rao-Blackwell improvement. This is illustrated via a simple example based on the uniform distribution, in which a rather natural Rao-Blackwell improvement is uniformly improvable. Furthermore, in this example the maximum likelihood estimator is inefficient, and an unbiased generalized Bayes estimator performs exceptionally well. Counterexamples of this sort can be useful didactic tools for explaining the true nature of a methodology and possible consequences when some of the assumptions are violated. [Received December 2014. Revised September 2015.].
Iliff, K. W.; Maine, R. E.
1976-01-01
A maximum likelihood estimation method was applied to flight data and procedures to facilitate the routine analysis of a large amount of flight data were described. Techniques that can be used to obtain stability and control derivatives from aircraft maneuvers that are less than ideal for this purpose are described. The techniques involve detecting and correcting the effects of dependent or nearly dependent variables, structural vibration, data drift, inadequate instrumentation, and difficulties with the data acquisition system and the mathematical model. The use of uncertainty levels and multiple maneuver analysis also proved to be useful in improving the quality of the estimated coefficients. The procedures used for editing the data and for overall analysis are also discussed.
International Nuclear Information System (INIS)
Metz, C.E.; Tokars, R.P.; Kronman, H.B.; Griem, M.L.
1982-01-01
A Therapeutic Operating Characteristic (TOC) curve for radiation therapy plots, for all possible treatment doses, the probability of tumor ablation as a function of the probability of radiation-induced complication. Application of this analysis to actual therapeutic situation requires that dose-response curves for ablation and for complication be estimated from clinical data. We describe an approach in which ''maximum likelihood estimates'' of these dose-response curves are made, and we apply this approach to data collected on responses to radiotherapy for carcinoma of the nasopharynx. TOC curves constructed from the estimated dose-response curves are subject to moderately large uncertainties because of the limitations of available data.These TOC curves suggest, however, that treatment doses greater than 1800 rem may substantially increase the probability of tumor ablation with little increase in the risk of radiation-induced cervical myelopathy, especially for T1 and T2 tumors
Tom, C. H.; Miller, L. D.
1984-01-01
The Bayesian maximum likelihood parametric classifier has been tested against the data-based formulation designated 'linear discrimination analysis', using the 'GLIKE' decision and "CLASSIFY' classification algorithms in the Landsat Mapping System. Identical supervised training sets, USGS land use/land cover classes, and various combinations of Landsat image and ancilliary geodata variables, were used to compare the algorithms' thematic mapping accuracy on a single-date summer subscene, with a cellularized USGS land use map of the same time frame furnishing the ground truth reference. CLASSIFY, which accepts a priori class probabilities, is found to be more accurate than GLIKE, which assumes equal class occurrences, for all three mapping variable sets and both levels of detail. These results may be generalized to direct accuracy, time, cost, and flexibility advantages of linear discriminant analysis over Bayesian methods.
Castrillon, Julio
2015-11-10
We develop a multi-level restricted Gaussian maximum likelihood method for estimating the covariance function parameters and computing the best unbiased predictor. Our approach produces a new set of multi-level contrasts where the deterministic parameters of the model are filtered out thus enabling the estimation of the covariance parameters to be decoupled from the deterministic component. Moreover, the multi-level covariance matrix of the contrasts exhibit fast decay that is dependent on the smoothness of the covariance function. Due to the fast decay of the multi-level covariance matrix coefficients only a small set is computed with a level dependent criterion. We demonstrate our approach on problems of up to 512,000 observations with a Matérn covariance function and highly irregular placements of the observations. In addition, these problems are numerically unstable and hard to solve with traditional methods.
International Nuclear Information System (INIS)
He, Yi; Scheraga, Harold A.; Liwo, Adam
2015-01-01
Coarse-grained models are useful tools to investigate the structural and thermodynamic properties of biomolecules. They are obtained by merging several atoms into one interaction site. Such simplified models try to capture as much as possible information of the original biomolecular system in all-atom representation but the resulting parameters of these coarse-grained force fields still need further optimization. In this paper, a force field optimization method, which is based on maximum-likelihood fitting of the simulated to the experimental conformational ensembles and least-squares fitting of the simulated to the experimental heat-capacity curves, is applied to optimize the Nucleic Acid united-RESidue 2-point (NARES-2P) model for coarse-grained simulations of nucleic acids recently developed in our laboratory. The optimized NARES-2P force field reproduces the structural and thermodynamic data of small DNA molecules much better than the original force field
Mavrodiev, Evgeny V; Laktionov, Alexy P; Cellinese, Nico
2012-01-01
The evolution of the diverse flora in the Lower Volga Valley (LVV) (southwest Russia) is complex due to the composite geomorphology and tectonic history of the Caspian Sea and adjacent areas. In the absence of phylogenetic studies and temporal information, we implemented a maximum likelihood (ML) approach and stochastic character mapping reconstruction aiming at recovering historical signals from species occurrence data. A taxon-area matrix of 13 floristic areas and 1018 extant species was constructed and analyzed with RAxML and Mesquite. Additionally, we simulated scenarios with numbers of hypothetical extinct taxa from an unknown palaeoflora that occupied the areas before the dramatic transgression and regression events that have occurred from the Pleistocene to the present day. The flora occurring strictly along the river valley and delta appear to be younger than that of adjacent steppes and desert-like regions, regardless of the chronology of transgression and regression events that led to the geomorphological formation of the LVV. This result is also supported when hypothetical extinct taxa are included in the analyses. The history of each species was inferred by using a stochastic character mapping reconstruction method as implemented in Mesquite. Individual histories appear to be independent from one another and have been shaped by repeated dispersal and extinction events. These reconstructions provide testable hypotheses for more in-depth investigations of their population structure and dynamics. PMID:22957179
Liu, Lihong; Xia, Hongyan; Baule, Claudia; Belák, Sándor
2009-01-01
Bovine viral diarrhoea virus 1 (BVDV-1) and Bovine viral diarrhoea virus 2 (BVDV-2) are two recognised bovine pestivirus species of the genus Pestivirus. Recently, a pestivirus, termed SVA/cont-08, was detected in a batch of contaminated foetal calf serum originating from South America. Comparative sequence analysis showed that the SVA/cont-08 virus shares 15-28% higher sequence identity to pestivirus D32/00_'HoBi' than to members of BVDV-1 and BVDV-2. In order to reveal the phylogenetic relationship of SVA/cont-08 with other pestiviruses, a molecular dataset of 30 pestiviruses and 1,896 characters, comprising the 5'UTR, N(pro) and E2 gene regions, was analysed by two methods: maximum likelihood and Bayesian approach. An identical, well-supported tree topology was observed, where four pestiviruses (SVA/cont-08, D32/00_'HoBi', CH-KaHo/cont, and Th/04_KhonKaen) formed a monophyletic clade that is closely related to the BVDV-1 and BVDV-2 clades. The strategy applied in this study is useful for classifying novel pestiviruses in the future.
Hamaker, Ellen L.; Dolan, Conor V.; Molenaar, Peter C. M.
2003-01-01
Demonstrated, through simulation, that stationary autoregressive moving average (ARMA) models may be fitted readily when T>N, using normal theory raw maximum likelihood structural equation modeling. Also provides some illustrations based on real data. (SLD)
Walker, H. F.
1976-01-01
Likelihood equations determined by the two types of samples which are necessary conditions for a maximum-likelihood estimate are considered. These equations, suggest certain successive-approximations iterative procedures for obtaining maximum-likelihood estimates. These are generalized steepest ascent (deflected gradient) procedures. It is shown that, with probability 1 as N sub 0 approaches infinity (regardless of the relative sizes of N sub 0 and N sub 1, i=1,...,m), these procedures converge locally to the strongly consistent maximum-likelihood estimates whenever the step size is between 0 and 2. Furthermore, the value of the step size which yields optimal local convergence rates is bounded from below by a number which always lies between 1 and 2.
Julien, Clavel; Leandro, Aristide; Hélène, Morlon
2018-06-19
Working with high-dimensional phylogenetic comparative datasets is challenging because likelihood-based multivariate methods suffer from low statistical performances as the number of traits p approaches the number of species n and because some computational complications occur when p exceeds n. Alternative phylogenetic comparative methods have recently been proposed to deal with the large p small n scenario but their use and performances are limited. Here we develop a penalized likelihood framework to deal with high-dimensional comparative datasets. We propose various penalizations and methods for selecting the intensity of the penalties. We apply this general framework to the estimation of parameters (the evolutionary trait covariance matrix and parameters of the evolutionary model) and model comparison for the high-dimensional multivariate Brownian (BM), Early-burst (EB), Ornstein-Uhlenbeck (OU) and Pagel's lambda models. We show using simulations that our penalized likelihood approach dramatically improves the estimation of evolutionary trait covariance matrices and model parameters when p approaches n, and allows for their accurate estimation when p equals or exceeds n. In addition, we show that penalized likelihood models can be efficiently compared using Generalized Information Criterion (GIC). We implement these methods, as well as the related estimation of ancestral states and the computation of phylogenetic PCA in the R package RPANDA and mvMORPH. Finally, we illustrate the utility of the new proposed framework by evaluating evolutionary models fit, analyzing integration patterns, and reconstructing evolutionary trajectories for a high-dimensional 3-D dataset of brain shape in the New World monkeys. We find a clear support for an Early-burst model suggesting an early diversification of brain morphology during the ecological radiation of the clade. Penalized likelihood offers an efficient way to deal with high-dimensional multivariate comparative data.
230Th and 234Th as coupled tracers of particle cycling in the ocean: A maximum likelihood approach
Wang, Wei-Lei; Armstrong, Robert A.; Cochran, J. Kirk; Heilbrun, Christina
2016-05-01
We applied maximum likelihood estimation to measurements of Th isotopes (234,230Th) in Mediterranean Sea sediment traps that separated particles according to settling velocity. This study contains two unique aspects. First, it relies on settling velocities that were measured using sediment traps, rather than on measured particle sizes and an assumed relationship between particle size and sinking velocity. Second, because of the labor and expense involved in obtaining these data, they were obtained at only a few depths, and their analysis required constructing a new type of box-like model, which we refer to as a "two-layer" model, that we then analyzed using likelihood techniques. Likelihood techniques were developed in the 1930s by statisticians, and form the computational core of both Bayesian and non-Bayesian statistics. Their use has recently become very popular in ecology, but they are relatively unknown in geochemistry. Our model was formulated by assuming steady state and first-order reaction kinetics for thorium adsorption and desorption, and for particle aggregation, disaggregation, and remineralization. We adopted a cutoff settling velocity (49 m/d) from Armstrong et al. (2009) to separate particles into fast- and slow-sinking classes. A unique set of parameters with no dependence on prior values was obtained. Adsorption rate constants for both slow- and fast-sinking particles are slightly higher in the upper layer than in the lower layer. Slow-sinking particles have higher adsorption rate constants than fast-sinking particles. Desorption rate constants are higher in the lower layer (slow-sinking particles: 13.17 ± 1.61, fast-sinking particles: 13.96 ± 0.48) than in the upper layer (slow-sinking particles: 7.87 ± 0.60 y-1, fast-sinking particles: 1.81 ± 0.44 y-1). Aggregation rate constants were higher, 1.88 ± 0.04, in the upper layer and just 0.07 ± 0.01 y-1 in the lower layer. Disaggregation rate constants were just 0.30 ± 0.10 y-1 in the upper
Eggers, G. L.; Lewis, K. W.; Simons, F. J.; Olhede, S.
2013-12-01
Venus does not possess a plate-tectonic system like that observed on Earth, and many surface features--such as tesserae and coronae--lack terrestrial equivalents. To understand Venus' tectonics is to understand its lithosphere, requiring a study of topography and gravity, and how they relate. Past studies of topography dealt with mapping and classification of visually observed features, and studies of gravity dealt with inverting the relation between topography and gravity anomalies to recover surface density and elastic thickness in either the space (correlation) or the spectral (admittance, coherence) domain. In the former case, geological features could be delineated but not classified quantitatively. In the latter case, rectangular or circular data windows were used, lacking geological definition. While the estimates of lithospheric strength on this basis were quantitative, they lacked robust error estimates. Here, we remapped the surface into 77 regions visually and qualitatively defined from a combination of Magellan topography, gravity, and radar images. We parameterize the spectral covariance of the observed topography, treating it as a Gaussian process assumed to be stationary over the mapped regions, using a three-parameter isotropic Matern model, and perform maximum-likelihood based inversions for the parameters. We discuss the parameter distribution across the Venusian surface and across terrain types such as coronoae, dorsae, tesserae, and their relation with mean elevation and latitudinal position. We find that the three-parameter model, while mathematically established and applicable to Venus topography, is overparameterized, and thus reduce the results to a two-parameter description of the peak spectral variance and the range-to-half-peak variance (in function of the wavenumber). With the reduction the clustering of geological region types in two-parameter space becomes promising. Finally, we perform inversions for the JOINT spectral variance of
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Salces Judit
2011-08-01
Full Text Available Abstract Background Reference genes with stable expression are required to normalize expression differences of target genes in qPCR experiments. Several procedures and companion software have been proposed to find the most stable genes. Model based procedures are attractive because they provide a solid statistical framework. NormFinder, a widely used software, uses a model based method. The pairwise comparison procedure implemented in GeNorm is a simpler procedure but one of the most extensively used. In the present work a statistical approach based in Maximum Likelihood estimation under mixed models was tested and compared with NormFinder and geNorm softwares. Sixteen candidate genes were tested in whole blood samples from control and heat stressed sheep. Results A model including gene and treatment as fixed effects, sample (animal, gene by treatment, gene by sample and treatment by sample interactions as random effects with heteroskedastic residual variance in gene by treatment levels was selected using goodness of fit and predictive ability criteria among a variety of models. Mean Square Error obtained under the selected model was used as indicator of gene expression stability. Genes top and bottom ranked by the three approaches were similar; however, notable differences for the best pair of genes selected for each method and the remaining genes of the rankings were shown. Differences among the expression values of normalized targets for each statistical approach were also found. Conclusions Optimal statistical properties of Maximum Likelihood estimation joined to mixed model flexibility allow for more accurate estimation of expression stability of genes under many different situations. Accurate selection of reference genes has a direct impact over the normalized expression values of a given target gene. This may be critical when the aim of the study is to compare expression rate differences among samples under different environmental
Papaconstadopoulos, P; Levesque, I R; Maglieri, R; Seuntjens, J
2016-02-07
Direct determination of the source intensity distribution of clinical linear accelerators is still a challenging problem for small field beam modeling. Current techniques most often involve special equipment and are difficult to implement in the clinic. In this work we present a maximum-likelihood expectation-maximization (MLEM) approach to the source reconstruction problem utilizing small fields and a simple experimental set-up. The MLEM algorithm iteratively ray-traces photons from the source plane to the exit plane and extracts corrections based on photon fluence profile measurements. The photon fluence profiles were determined by dose profile film measurements in air using a high density thin foil as build-up material and an appropriate point spread function (PSF). The effect of other beam parameters and scatter sources was minimized by using the smallest field size ([Formula: see text] cm(2)). The source occlusion effect was reproduced by estimating the position of the collimating jaws during this process. The method was first benchmarked against simulations for a range of typical accelerator source sizes. The sources were reconstructed with an accuracy better than 0.12 mm in the full width at half maximum (FWHM) to the respective electron sources incident on the target. The estimated jaw positions agreed within 0.2 mm with the expected values. The reconstruction technique was also tested against measurements on a Varian Novalis Tx linear accelerator and compared to a previously commissioned Monte Carlo model. The reconstructed FWHM of the source agreed within 0.03 mm and 0.11 mm to the commissioned electron source in the crossplane and inplane orientations respectively. The impact of the jaw positioning, experimental and PSF uncertainties on the reconstructed source distribution was evaluated with the former presenting the dominant effect.
International Nuclear Information System (INIS)
Veklerov, E.; Llacer, J.; Hoffman, E.J.
1987-10-01
In order to study properties of the Maximum Likelihood Estimator (MLE) algorithm for image reconstruction in Positron Emission Tomographyy (PET), the algorithm is applied to data obtained by the ECAT-III tomograph from a brain phantom. The procedure for subtracting accidental coincidences from the data stream generated by this physical phantom is such that he resultant data are not Poisson distributed. This makes the present investigation different from other investigations based on computer-simulated phantoms. It is shown that the MLE algorithm is robust enough to yield comparatively good images, especially when the phantom is in the periphery of the field of view, even though the underlying assumption of the algorithm is violated. Two transition matrices are utilized. The first uses geometric considerations only. The second is derived by a Monte Carlo simulation which takes into account Compton scattering in the detectors, positron range, etc. in the detectors. It is demonstrated that the images obtained from the Monte Carlo matrix are superior in some specific ways. A stopping rule derived earlier and allowing the user to stop the iterative process before the images begin to deteriorate is tested. Since the rule is based on the Poisson assumption, it does not work well with the presently available data, although it is successful wit computer-simulated Poisson data
Lin, Jen-Jen; Cheng, Jung-Yu; Huang, Li-Fei; Lin, Ying-Hsiu; Wan, Yung-Liang; Tsui, Po-Hsiang
2017-05-01
The Nakagami distribution is an approximation useful to the statistics of ultrasound backscattered signals for tissue characterization. Various estimators may affect the Nakagami parameter in the detection of changes in backscattered statistics. In particular, the moment-based estimator (MBE) and maximum likelihood estimator (MLE) are two primary methods used to estimate the Nakagami parameters of ultrasound signals. This study explored the effects of the MBE and different MLE approximations on Nakagami parameter estimations. Ultrasound backscattered signals of different scatterer number densities were generated using a simulation model, and phantom experiments and measurements of human liver tissues were also conducted to acquire real backscattered echoes. Envelope signals were employed to estimate the Nakagami parameters by using the MBE, first- and second-order approximations of MLE (MLE 1 and MLE 2 , respectively), and Greenwood approximation (MLE gw ) for comparisons. The simulation results demonstrated that, compared with the MBE and MLE 1 , the MLE 2 and MLE gw enabled more stable parameter estimations with small sample sizes. Notably, the required data length of the envelope signal was 3.6 times the pulse length. The phantom and tissue measurement results also showed that the Nakagami parameters estimated using the MLE 2 and MLE gw could simultaneously differentiate various scatterer concentrations with lower standard deviations and reliably reflect physical meanings associated with the backscattered statistics. Therefore, the MLE 2 and MLE gw are suggested as estimators for the development of Nakagami-based methodologies for ultrasound tissue characterization. Copyright © 2017 Elsevier B.V. All rights reserved.
Kim, Kyungsoo; Lim, Sung-Ho; Lee, Jaeseok; Kang, Won-Seok; Moon, Cheil; Choi, Ji-Woong
2016-01-01
Electroencephalograms (EEGs) measure a brain signal that contains abundant information about the human brain function and health. For this reason, recent clinical brain research and brain computer interface (BCI) studies use EEG signals in many applications. Due to the significant noise in EEG traces, signal processing to enhance the signal to noise power ratio (SNR) is necessary for EEG analysis, especially for non-invasive EEG. A typical method to improve the SNR is averaging many trials of event related potential (ERP) signal that represents a brain’s response to a particular stimulus or a task. The averaging, however, is very sensitive to variable delays. In this study, we propose two time delay estimation (TDE) schemes based on a joint maximum likelihood (ML) criterion to compensate the uncertain delays which may be different in each trial. We evaluate the performance for different types of signals such as random, deterministic, and real EEG signals. The results show that the proposed schemes provide better performance than other conventional schemes employing averaged signal as a reference, e.g., up to 4 dB gain at the expected delay error of 10°. PMID:27322267
Directory of Open Access Journals (Sweden)
Kyungsoo Kim
2016-06-01
Full Text Available Electroencephalograms (EEGs measure a brain signal that contains abundant information about the human brain function and health. For this reason, recent clinical brain research and brain computer interface (BCI studies use EEG signals in many applications. Due to the significant noise in EEG traces, signal processing to enhance the signal to noise power ratio (SNR is necessary for EEG analysis, especially for non-invasive EEG. A typical method to improve the SNR is averaging many trials of event related potential (ERP signal that represents a brain’s response to a particular stimulus or a task. The averaging, however, is very sensitive to variable delays. In this study, we propose two time delay estimation (TDE schemes based on a joint maximum likelihood (ML criterion to compensate the uncertain delays which may be different in each trial. We evaluate the performance for different types of signals such as random, deterministic, and real EEG signals. The results show that the proposed schemes provide better performance than other conventional schemes employing averaged signal as a reference, e.g., up to 4 dB gain at the expected delay error of 10°.
Craciunescu, Teddy; Peluso, Emmanuele; Murari, Andrea; Gelfusa, Michela; JET Contributors
2018-05-01
The total emission of radiation is a crucial quantity to calculate the power balances and to understand the physics of any Tokamak. Bolometric systems are the main tool to measure this important physical quantity through quite sophisticated tomographic inversion methods. On the Joint European Torus, the coverage of the bolometric diagnostic, due to the availability of basically only two projection angles, is quite limited, rendering the inversion a very ill-posed mathematical problem. A new approach, based on the maximum likelihood, has therefore been developed and implemented to alleviate one of the major weaknesses of traditional tomographic techniques: the difficulty to determine routinely the confidence intervals in the results. The method has been validated by numerical simulations with phantoms to assess the quality of the results and to optimise the configuration of the parameters for the main types of emissivity encountered experimentally. The typical levels of statistical errors, which may significantly influence the quality of the reconstructions, have been identified. The systematic tests with phantoms indicate that the errors in the reconstructions are quite limited and their effect on the total radiated power remains well below 10%. A comparison with other approaches to the inversion and to the regularization has also been performed.
Wang, Kezhi
2014-10-01
Bit error rate (BER) and outage probability for amplify-and-forward (AF) relaying systems with two different channel estimation methods, disintegrated channel estimation and cascaded channel estimation, using pilot-aided maximum likelihood method in slowly fading Rayleigh channels are derived. Based on the BERs, the optimal values of pilot power under the total transmitting power constraints at the source and the optimal values of pilot power under the total transmitting power constraints at the relay are obtained, separately. Moreover, the optimal power allocation between the pilot power at the source, the pilot power at the relay, the data power at the source and the data power at the relay are obtained when their total transmitting power is fixed. Numerical results show that the derived BER expressions match with the simulation results. They also show that the proposed systems with optimal power allocation outperform the conventional systems without power allocation under the same other conditions. In some cases, the gain could be as large as several dB\\'s in effective signal-to-noise ratio.
Energy Technology Data Exchange (ETDEWEB)
Raghunathan, Srinivasan; Patil, Sanjaykumar; Bianchini, Federico; Reichardt, Christian L. [School of Physics, University of Melbourne, 313 David Caro building, Swanston St and Tin Alley, Parkville VIC 3010 (Australia); Baxter, Eric J. [Department of Physics and Astronomy, University of Pennsylvania, 209 S. 33rd Street, Philadelphia, PA 19104 (United States); Bleem, Lindsey E. [Argonne National Laboratory, High-Energy Physics Division, 9700 S. Cass Avenue, Argonne, IL 60439 (United States); Crawford, Thomas M. [Kavli Institute for Cosmological Physics, University of Chicago, 5640 South Ellis Avenue, Chicago, IL 60637 (United States); Holder, Gilbert P. [Department of Astronomy and Department of Physics, University of Illinois, 1002 West Green St., Urbana, IL 61801 (United States); Manzotti, Alessandro, E-mail: srinivasan.raghunathan@unimelb.edu.au, E-mail: s.patil2@student.unimelb.edu.au, E-mail: ebax@sas.upenn.edu, E-mail: federico.bianchini@unimelb.edu.au, E-mail: bleeml@uchicago.edu, E-mail: tcrawfor@kicp.uchicago.edu, E-mail: gholder@illinois.edu, E-mail: manzotti@uchicago.edu, E-mail: christian.reichardt@unimelb.edu.au [Department of Astronomy and Astrophysics, University of Chicago, 5640 South Ellis Avenue, Chicago, IL 60637 (United States)
2017-08-01
We develop a Maximum Likelihood estimator (MLE) to measure the masses of galaxy clusters through the impact of gravitational lensing on the temperature and polarization anisotropies of the cosmic microwave background (CMB). We show that, at low noise levels in temperature, this optimal estimator outperforms the standard quadratic estimator by a factor of two. For polarization, we show that the Stokes Q/U maps can be used instead of the traditional E- and B-mode maps without losing information. We test and quantify the bias in the recovered lensing mass for a comprehensive list of potential systematic errors. Using realistic simulations, we examine the cluster mass uncertainties from CMB-cluster lensing as a function of an experiment's beam size and noise level. We predict the cluster mass uncertainties will be 3 - 6% for SPT-3G, AdvACT, and Simons Array experiments with 10,000 clusters and less than 1% for the CMB-S4 experiment with a sample containing 100,000 clusters. The mass constraints from CMB polarization are very sensitive to the experimental beam size and map noise level: for a factor of three reduction in either the beam size or noise level, the lensing signal-to-noise improves by roughly a factor of two.
Lusiana, Evellin Dewi
2017-12-01
The parameters of binary probit regression model are commonly estimated by using Maximum Likelihood Estimation (MLE) method. However, MLE method has limitation if the binary data contains separation. Separation is the condition where there are one or several independent variables that exactly grouped the categories in binary response. It will result the estimators of MLE method become non-convergent, so that they cannot be used in modeling. One of the effort to resolve the separation is using Firths approach instead. This research has two aims. First, to identify the chance of separation occurrence in binary probit regression model between MLE method and Firths approach. Second, to compare the performance of binary probit regression model estimator that obtained by MLE method and Firths approach using RMSE criteria. Those are performed using simulation method and under different sample size. The results showed that the chance of separation occurrence in MLE method for small sample size is higher than Firths approach. On the other hand, for larger sample size, the probability decreased and relatively identic between MLE method and Firths approach. Meanwhile, Firths estimators have smaller RMSE than MLEs especially for smaller sample sizes. But for larger sample sizes, the RMSEs are not much different. It means that Firths estimators outperformed MLE estimator.
Energy Technology Data Exchange (ETDEWEB)
Price, Oliver R., E-mail: oliver.price@unilever.co [Warwick-HRI, University of Warwick, Wellesbourne, Warwick, CV32 6EF (United Kingdom); University of Reading, Soil Science Department, Whiteknights, Reading, RG6 6UR (United Kingdom); Oliver, Margaret A. [University of Reading, Soil Science Department, Whiteknights, Reading, RG6 6UR (United Kingdom); Walker, Allan [Warwick-HRI, University of Warwick, Wellesbourne, Warwick, CV32 6EF (United Kingdom); Wood, Martin [University of Reading, Soil Science Department, Whiteknights, Reading, RG6 6UR (United Kingdom)
2009-05-15
An unbalanced nested sampling design was used to investigate the spatial scale of soil and herbicide interactions at the field scale. A hierarchical analysis of variance based on residual maximum likelihood (REML) was used to analyse the data and provide a first estimate of the variogram. Soil samples were taken at 108 locations at a range of separating distances in a 9 ha field to explore small and medium scale spatial variation. Soil organic matter content, pH, particle size distribution, microbial biomass and the degradation and sorption of the herbicide, isoproturon, were determined for each soil sample. A large proportion of the spatial variation in isoproturon degradation and sorption occurred at sampling intervals less than 60 m, however, the sampling design did not resolve the variation present at scales greater than this. A sampling interval of 20-25 m should ensure that the main spatial structures are identified for isoproturon degradation rate and sorption without too great a loss of information in this field. - Estimating the spatial scale of herbicide and soil interactions by nested sampling.
International Nuclear Information System (INIS)
Price, Oliver R.; Oliver, Margaret A.; Walker, Allan; Wood, Martin
2009-01-01
An unbalanced nested sampling design was used to investigate the spatial scale of soil and herbicide interactions at the field scale. A hierarchical analysis of variance based on residual maximum likelihood (REML) was used to analyse the data and provide a first estimate of the variogram. Soil samples were taken at 108 locations at a range of separating distances in a 9 ha field to explore small and medium scale spatial variation. Soil organic matter content, pH, particle size distribution, microbial biomass and the degradation and sorption of the herbicide, isoproturon, were determined for each soil sample. A large proportion of the spatial variation in isoproturon degradation and sorption occurred at sampling intervals less than 60 m, however, the sampling design did not resolve the variation present at scales greater than this. A sampling interval of 20-25 m should ensure that the main spatial structures are identified for isoproturon degradation rate and sorption without too great a loss of information in this field. - Estimating the spatial scale of herbicide and soil interactions by nested sampling.
Yang, Li; Wang, Guobao; Qi, Jinyi
2016-04-01
Detecting cancerous lesions is a major clinical application of emission tomography. In a previous work, we studied penalized maximum-likelihood (PML) image reconstruction for lesion detection in static PET. Here we extend our theoretical analysis of static PET reconstruction to dynamic PET. We study both the conventional indirect reconstruction and direct reconstruction for Patlak parametric image estimation. In indirect reconstruction, Patlak parametric images are generated by first reconstructing a sequence of dynamic PET images, and then performing Patlak analysis on the time activity curves (TACs) pixel-by-pixel. In direct reconstruction, Patlak parametric images are estimated directly from raw sinogram data by incorporating the Patlak model into the image reconstruction procedure. PML reconstruction is used in both the indirect and direct reconstruction methods. We use a channelized Hotelling observer (CHO) to assess lesion detectability in Patlak parametric images. Simplified expressions for evaluating the lesion detectability have been derived and applied to the selection of the regularization parameter value to maximize detection performance. The proposed method is validated using computer-based Monte Carlo simulations. Good agreements between the theoretical predictions and the Monte Carlo results are observed. Both theoretical predictions and Monte Carlo simulation results show the benefit of the indirect and direct methods under optimized regularization parameters in dynamic PET reconstruction for lesion detection, when compared with the conventional static PET reconstruction.
International Nuclear Information System (INIS)
Llacer, J.; Veklerov, E.; Nolan, D.; Grafton, S.T.; Mazziotta, J.C.; Hawkins, R.A.; Hoh, C.K.; Hoffman, E.J.
1990-10-01
This paper will report on the progress to date in carrying out Receiver Operating Characteristics (ROC) studies comparing Maximum Likelihood Estimator (MLE) and Filtered Backprojection (FBP) reconstructions of normal and abnormal human brain PET data in a clinical setting. A previous statistical study of reconstructions of the Hoffman brain phantom with real data indicated that the pixel-to-pixel standard deviation in feasible MLE images is approximately proportional to the square root of the number of counts in a region, as opposed to a standard deviation which is high and largely independent of the number of counts in FBP. A preliminary ROC study carried out with 10 non-medical observers performing a relatively simple detectability task indicates that, for the majority of observers, lower standard deviation translates itself into a statistically significant detectability advantage in MLE reconstructions. The initial results of ongoing tests with four experienced neurologists/nuclear medicine physicians are presented. Normal cases of 18 F -- fluorodeoxyglucose (FDG) cerebral metabolism studies and abnormal cases in which a variety of lesions have been introduced into normal data sets have been evaluated. We report on the results of reading the reconstructions of 90 data sets, each corresponding to a single brain slice. It has become apparent that the design of the study based on reading single brain slices is too insensitive and we propose a variation based on reading three consecutive slices at a time, rating only the center slice. 9 refs., 2 figs., 1 tab
Wang, Kezhi; Chen, Yunfei; Alouini, Mohamed-Slim; Xu, Feng
2014-01-01
Bit error rate (BER) and outage probability for amplify-and-forward (AF) relaying systems with two different channel estimation methods, disintegrated channel estimation and cascaded channel estimation, using pilot-aided maximum likelihood method in slowly fading Rayleigh channels are derived. Based on the BERs, the optimal values of pilot power under the total transmitting power constraints at the source and the optimal values of pilot power under the total transmitting power constraints at the relay are obtained, separately. Moreover, the optimal power allocation between the pilot power at the source, the pilot power at the relay, the data power at the source and the data power at the relay are obtained when their total transmitting power is fixed. Numerical results show that the derived BER expressions match with the simulation results. They also show that the proposed systems with optimal power allocation outperform the conventional systems without power allocation under the same other conditions. In some cases, the gain could be as large as several dB's in effective signal-to-noise ratio.
Deville, Yannick; Deville, Alain
2009-01-01
In a previous paper [1], we investigated the Blind Source Separation (BSS) problem, for the nonlinear mixing model that we introduced in that paper. We proposed to solve this problem by using a maximum likelihood (ML) approach. When applying the ML approach to BSS problems, one usually determines the analytical expressions of the derivatives of the log-likelihood with respect to the parameters of the considered mixing model. In the literature, these calculations were mainly considered for lin...
Helaers, Raphaël; Milinkovitch, Michel C
2010-07-15
The development, in the last decade, of stochastic heuristics implemented in robust application softwares has made large phylogeny inference a key step in most comparative studies involving molecular sequences. Still, the choice of a phylogeny inference software is often dictated by a combination of parameters not related to the raw performance of the implemented algorithm(s) but rather by practical issues such as ergonomics and/or the availability of specific functionalities. Here, we present MetaPIGA v2.0, a robust implementation of several stochastic heuristics for large phylogeny inference (under maximum likelihood), including a Simulated Annealing algorithm, a classical Genetic Algorithm, and the Metapopulation Genetic Algorithm (metaGA) together with complex substitution models, discrete Gamma rate heterogeneity, and the possibility to partition data. MetaPIGA v2.0 also implements the Likelihood Ratio Test, the Akaike Information Criterion, and the Bayesian Information Criterion for automated selection of substitution models that best fit the data. Heuristics and substitution models are highly customizable through manual batch files and command line processing. However, MetaPIGA v2.0 also offers an extensive graphical user interface for parameters setting, generating and running batch files, following run progress, and manipulating result trees. MetaPIGA v2.0 uses standard formats for data sets and trees, is platform independent, runs in 32 and 64-bits systems, and takes advantage of multiprocessor and multicore computers. The metaGA resolves the major problem inherent to classical Genetic Algorithms by maintaining high inter-population variation even under strong intra-population selection. Implementation of the metaGA together with additional stochastic heuristics into a single software will allow rigorous optimization of each heuristic as well as a meaningful comparison of performances among these algorithms. MetaPIGA v2.0 gives access both to high
Directory of Open Access Journals (Sweden)
Milinkovitch Michel C
2010-07-01
Full Text Available Abstract Background The development, in the last decade, of stochastic heuristics implemented in robust application softwares has made large phylogeny inference a key step in most comparative studies involving molecular sequences. Still, the choice of a phylogeny inference software is often dictated by a combination of parameters not related to the raw performance of the implemented algorithm(s but rather by practical issues such as ergonomics and/or the availability of specific functionalities. Results Here, we present MetaPIGA v2.0, a robust implementation of several stochastic heuristics for large phylogeny inference (under maximum likelihood, including a Simulated Annealing algorithm, a classical Genetic Algorithm, and the Metapopulation Genetic Algorithm (metaGA together with complex substitution models, discrete Gamma rate heterogeneity, and the possibility to partition data. MetaPIGA v2.0 also implements the Likelihood Ratio Test, the Akaike Information Criterion, and the Bayesian Information Criterion for automated selection of substitution models that best fit the data. Heuristics and substitution models are highly customizable through manual batch files and command line processing. However, MetaPIGA v2.0 also offers an extensive graphical user interface for parameters setting, generating and running batch files, following run progress, and manipulating result trees. MetaPIGA v2.0 uses standard formats for data sets and trees, is platform independent, runs in 32 and 64-bits systems, and takes advantage of multiprocessor and multicore computers. Conclusions The metaGA resolves the major problem inherent to classical Genetic Algorithms by maintaining high inter-population variation even under strong intra-population selection. Implementation of the metaGA together with additional stochastic heuristics into a single software will allow rigorous optimization of each heuristic as well as a meaningful comparison of performances among these
Phylogenetic Trees From Sequences
Ryvkin, Paul; Wang, Li-San
In this chapter, we review important concepts and approaches for phylogeny reconstruction from sequence data.We first cover some basic definitions and properties of phylogenetics, and briefly explain how scientists model sequence evolution and measure sequence divergence. We then discuss three major approaches for phylogenetic reconstruction: distance-based phylogenetic reconstruction, maximum parsimony, and maximum likelihood. In the third part of the chapter, we review how multiple phylogenies are compared by consensus methods and how to assess confidence using bootstrapping. At the end of the chapter are two sections that list popular software packages and additional reading.
International Nuclear Information System (INIS)
Arab, M.N.; Ayaz, M.
2004-01-01
The performance of transmission line insulator is greatly affected by dust, fumes from industrial areas and saline deposit near the coast. Such pollutants in the presence of moisture form a coating on the surface of the insulator, which in turn allows the passage of leakage current. This leakage builds up to a point where flashover develops. The flashover is often followed by permanent failure of insulation resulting in prolong outages. With the increase in system voltage owing to the greater demand of electrical energy over the past few decades, the importance of flashover due to pollution has received special attention. The objective of the present work was to study the performance of overhead line insulators in the presence of contaminants such as induced salts. A detailed review of the literature and the mechanisms of insulator flashover due to the pollution are presented. Experimental investigations on the behavior of overhead line insulators under industrial salt contamination are carried out. A special fog chamber was designed in which the contamination testing of insulators was carried out. Flashover behavior under various degrees of contamination of insulators with the most common industrial fume components such as Nitrate and Sulphate compounds was studied. Substituting the normal distribution parameter in the probability distribution function based on maximum likelihood develops a statistical method. The method gives a high accuracy in the estimation of the 50% flashover voltage, which is then used to evaluate the critical flashover index at various contamination levels. The critical flashover index is a valuable parameter in insulation design for numerous applications. (author)
Energy Technology Data Exchange (ETDEWEB)
Hogden, J.
1996-11-05
The goal of the proposed research is to test a statistical model of speech recognition that incorporates the knowledge that speech is produced by relatively slow motions of the tongue, lips, and other speech articulators. This model is called Maximum Likelihood Continuity Mapping (Malcom). Many speech researchers believe that by using constraints imposed by articulator motions, we can improve or replace the current hidden Markov model based speech recognition algorithms. Unfortunately, previous efforts to incorporate information about articulation into speech recognition algorithms have suffered because (1) slight inaccuracies in our knowledge or the formulation of our knowledge about articulation may decrease recognition performance, (2) small changes in the assumptions underlying models of speech production can lead to large changes in the speech derived from the models, and (3) collecting measurements of human articulator positions in sufficient quantity for training a speech recognition algorithm is still impractical. The most interesting (and in fact, unique) quality of Malcom is that, even though Malcom makes use of a mapping between acoustics and articulation, Malcom can be trained to recognize speech using only acoustic data. By learning the mapping between acoustics and articulation using only acoustic data, Malcom avoids the difficulties involved in collecting articulator position measurements and does not require an articulatory synthesizer model to estimate the mapping between vocal tract shapes and speech acoustics. Preliminary experiments that demonstrate that Malcom can learn the mapping between acoustics and articulation are discussed. Potential applications of Malcom aside from speech recognition are also discussed. Finally, specific deliverables resulting from the proposed research are described.
Directory of Open Access Journals (Sweden)
Kaarina Matilainen
Full Text Available Estimation of variance components by Monte Carlo (MC expectation maximization (EM restricted maximum likelihood (REML is computationally efficient for large data sets and complex linear mixed effects models. However, efficiency may be lost due to the need for a large number of iterations of the EM algorithm. To decrease the computing time we explored the use of faster converging Newton-type algorithms within MC REML implementations. The implemented algorithms were: MC Newton-Raphson (NR, where the information matrix was generated via sampling; MC average information(AI, where the information was computed as an average of observed and expected information; and MC Broyden's method, where the zero of the gradient was searched using a quasi-Newton-type algorithm. Performance of these algorithms was evaluated using simulated data. The final estimates were in good agreement with corresponding analytical ones. MC NR REML and MC AI REML enhanced convergence compared to MC EM REML and gave standard errors for the estimates as a by-product. MC NR REML required a larger number of MC samples, while each MC AI REML iteration demanded extra solving of mixed model equations by the number of parameters to be estimated. MC Broyden's method required the largest number of MC samples with our small data and did not give standard errors for the parameters directly. We studied the performance of three different convergence criteria for the MC AI REML algorithm. Our results indicate the importance of defining a suitable convergence criterion and critical value in order to obtain an efficient Newton-type method utilizing a MC algorithm. Overall, use of a MC algorithm with Newton-type methods proved feasible and the results encourage testing of these methods with different kinds of large-scale problem settings.
Sivaguru, Mayandi; Kabir, Mohammad M.; Gartia, Manas Ranjan; Biggs, David S. C.; Sivaguru, Barghav S.; Sivaguru, Vignesh A.; Berent, Zachary T.; Wagoner Johnson, Amy J.; Fried, Glenn A.; Liu, Gang Logan; Sadayappan, Sakthivel; Toussaint, Kimani C.
2017-02-01
Second-harmonic generation (SHG) microscopy is a label-free imaging technique to study collagenous materials in extracellular matrix environment with high resolution and contrast. However, like many other microscopy techniques, the actual spatial resolution achievable by SHG microscopy is reduced by out-of-focus blur and optical aberrations that degrade particularly the amplitude of the detectable higher spatial frequencies. Being a two-photon scattering process, it is challenging to define a point spread function (PSF) for the SHG imaging modality. As a result, in comparison with other two-photon imaging systems like two-photon fluorescence, it is difficult to apply any PSF-engineering techniques to enhance the experimental spatial resolution closer to the diffraction limit. Here, we present a method to improve the spatial resolution in SHG microscopy using an advanced maximum likelihood estimation (AdvMLE) algorithm to recover the otherwise degraded higher spatial frequencies in an SHG image. Through adaptation and iteration, the AdvMLE algorithm calculates an improved PSF for an SHG image and enhances the spatial resolution by decreasing the full-width-at-halfmaximum (FWHM) by 20%. Similar results are consistently observed for biological tissues with varying SHG sources, such as gold nanoparticles and collagen in porcine feet tendons. By obtaining an experimental transverse spatial resolution of 400 nm, we show that the AdvMLE algorithm brings the practical spatial resolution closer to the theoretical diffraction limit. Our approach is suitable for adaptation in micro-nano CT and MRI imaging, which has the potential to impact diagnosis and treatment of human diseases.
Wang, Chaolong; Schroeder, Kari B.; Rosenberg, Noah A.
2012-01-01
Allelic dropout is a commonly observed source of missing data in microsatellite genotypes, in which one or both allelic copies at a locus fail to be amplified by the polymerase chain reaction. Especially for samples with poor DNA quality, this problem causes a downward bias in estimates of observed heterozygosity and an upward bias in estimates of inbreeding, owing to mistaken classifications of heterozygotes as homozygotes when one of the two copies drops out. One general approach for avoiding allelic dropout involves repeated genotyping of homozygous loci to minimize the effects of experimental error. Existing computational alternatives often require replicate genotyping as well. These approaches, however, are costly and are suitable only when enough DNA is available for repeated genotyping. In this study, we propose a maximum-likelihood approach together with an expectation-maximization algorithm to jointly estimate allelic dropout rates and allele frequencies when only one set of nonreplicated genotypes is available. Our method considers estimates of allelic dropout caused by both sample-specific factors and locus-specific factors, and it allows for deviation from Hardy–Weinberg equilibrium owing to inbreeding. Using the estimated parameters, we correct the bias in the estimation of observed heterozygosity through the use of multiple imputations of alleles in cases where dropout might have occurred. With simulated data, we show that our method can (1) effectively reproduce patterns of missing data and heterozygosity observed in real data; (2) correctly estimate model parameters, including sample-specific dropout rates, locus-specific dropout rates, and the inbreeding coefficient; and (3) successfully correct the downward bias in estimating the observed heterozygosity. We find that our method is fairly robust to violations of model assumptions caused by population structure and by genotyping errors from sources other than allelic dropout. Because the data sets
A Maximum Parsimony Model to Reconstruct Phylogenetic Network in Honey Bee Evolution
Usha Chouhan; K. R. Pardasani
2007-01-01
Phylogenies ; The evolutionary histories of groups of species are one of the most widely used tools throughout the life sciences, as well as objects of research with in systematic, evolutionary biology. In every phylogenetic analysis reconstruction produces trees. These trees represent the evolutionary histories of many groups of organisms, bacteria due to horizontal gene transfer and plants due to process of hybridization. The process of gene transfer in bacteria and hyb...
International Nuclear Information System (INIS)
Lowrey, Justin D.; Biegalski, Steven R.F.
2012-01-01
The spectrum deconvolution analysis tool (SDAT) software code was written and tested at The University of Texas at Austin utilizing the standard spectrum technique to determine activity levels of Xe-131m, Xe-133m, Xe-133, and Xe-135 in β–γ coincidence spectra. SDAT was originally written to utilize the method of least-squares to calculate the activity of each radionuclide component in the spectrum. Recently, maximum likelihood estimation was also incorporated into the SDAT tool. This is a robust statistical technique to determine the parameters that maximize the Poisson distribution likelihood function of the sample data. In this case it is used to parameterize the activity level of each of the radioxenon components in the spectra. A new test dataset was constructed utilizing Xe-131m placed on a Xe-133 background to compare the robustness of the least-squares and maximum likelihood estimation methods for low counting statistics data. The Xe-131m spectra were collected independently from the Xe-133 spectra and added to generate the spectra in the test dataset. The true independent counts of Xe-131m and Xe-133 are known, as they were calculated before the spectra were added together. Spectra with both high and low counting statistics are analyzed. Studies are also performed by analyzing only the 30 keV X-ray region of the β–γ coincidence spectra. Results show that maximum likelihood estimation slightly outperforms least-squares for low counting statistics data.
International Nuclear Information System (INIS)
Goldman, A.S.; Beedgen, R.
1982-01-01
The investigation of data falsification and/or diversion is of major concern in nuclear materials accounting procedures used in international safeguards. In this paper, two procedures, denoted by (D,MUF) and LR (Likelihood Ratio), are discussed and compared when testing the hypothesis that neither diversion nor falsification has taken place versus the one-sided alternative that at least one of these parameters is positive. Critical regions and detection probabilities are given for both tests. It is shown that the LR method outperforms (D,MUF) when diversion and falsification take place
DEFF Research Database (Denmark)
Cavaliere, Giuseppe; Nielsen, Morten Ørregaard; Taylor, Robert
We consider the problem of conducting estimation and inference on the parameters of univariate heteroskedastic fractionally integrated time series models. We first extend existing results in the literature, developed for conditional sum-of squares estimators in the context of parametric fractional...... time series models driven by conditionally homoskedastic shocks, to allow for conditional and unconditional heteroskedasticity both of a quite general and unknown form. Global consistency and asymptotic normality are shown to still obtain; however, the covariance matrix of the limiting distribution...... of the estimator now depends on nuisance parameters derived both from the weak dependence and heteroskedasticity present in the shocks. We then investigate classical methods of inference based on the Wald, likelihood ratio and Lagrange multiplier tests for linear hypotheses on either or both of the long and short...
phangorn: phylogenetic analysis in R.
Schliep, Klaus Peter
2011-02-15
phangorn is a package for phylogenetic reconstruction and analysis in the R language. Previously it was only possible to estimate phylogenetic trees with distance methods in R. phangorn, now offers the possibility of reconstructing phylogenies with distance based methods, maximum parsimony or maximum likelihood (ML) and performing Hadamard conjugation. Extending the general ML framework, this package provides the possibility of estimating mixture and partition models. Furthermore, phangorn offers several functions for comparing trees, phylogenetic models or splits, simulating character data and performing congruence analyses. phangorn can be obtained through the CRAN homepage http://cran.r-project.org/web/packages/phangorn/index.html. phangorn is licensed under GPL 2.
PTree: pattern-based, stochastic search for maximum parsimony phylogenies
Gregor, Ivan; Steinbr?ck, Lars; McHardy, Alice C.
2013-01-01
Phylogenetic reconstruction is vital to analyzing the evolutionary relationship of genes within and across populations of different species. Nowadays, with next generation sequencing technologies producing sets comprising thousands of sequences, robust identification of the tree topology, which is optimal according to standard criteria such as maximum parsimony, maximum likelihood or posterior probability, with phylogenetic inference methods is a computationally very demanding task. Here, we ...
A Multi-Criterion Evolutionary Approach Applied to Phylogenetic Reconstruction
Cancino, W.; Delbem, A.C.B.
2010-01-01
In this paper, we proposed an MOEA approach, called PhyloMOEA which solves the phylogenetic inference problem using maximum parsimony and maximum likelihood criteria. The PhyloMOEA's development was motivated by several studies in the literature (Huelsenbeck, 1995; Jin & Nei, 1990; Kuhner & Felsenstein, 1994; Tateno et al., 1994), which point out that various phylogenetic inference methods lead to inconsistent solutions. Techniques using parsimony and likelihood criteria yield to different tr...
Kyle, H. Lee; Hucek, Richard R.; Groveman, Brian; Frey, Richard
1990-01-01
The archived Earth radiation budget (ERB) products produced from the Nimbus-7 ERB narrow field-of-view scanner are described. The principal products are broadband outgoing longwave radiation (4.5 to 50 microns), reflected solar radiation (0.2 to 4.8 microns), and the net radiation. Daily and monthly averages are presented on a fixed global equal area (500 sq km), grid for the period May 1979 to May 1980. Two independent algorithms are used to estimate the outgoing fluxes from the observed radiances. The algorithms are described and the results compared. The products are divided into three subsets: the Scene Radiance Tapes (SRT) contain the calibrated radiances; the Sorting into Angular Bins (SAB) tape contains the SAB produced shortwave, longwave, and net radiation products; and the Maximum Likelihood Cloud Estimation (MLCE) tapes contain the MLCE products. The tape formats are described in detail.
Onuk, A. Emre; Akcakaya, Murat; Bardhan, Jaydeep P.; Erdogmus, Deniz; Brooks, Dana H.; Makowski, Lee
2015-01-01
In this paper, we describe a model for maximum likelihood estimation (MLE) of the relative abundances of different conformations of a protein in a heterogeneous mixture from small angle X-ray scattering (SAXS) intensities. To consider cases where the solution includes intermediate or unknown conformations, we develop a subset selection method based on k-means clustering and the Cramér-Rao bound on the mixture coefficient estimation error to find a sparse basis set that represents the space spanned by the measured SAXS intensities of the known conformations of a protein. Then, using the selected basis set and the assumptions on the model for the intensity measurements, we show that the MLE model can be expressed as a constrained convex optimization problem. Employing the adenylate kinase (ADK) protein and its known conformations as an example, and using Monte Carlo simulations, we demonstrate the performance of the proposed estimation scheme. Here, although we use 45 crystallographically determined experimental structures and we could generate many more using, for instance, molecular dynamics calculations, the clustering technique indicates that the data cannot support the determination of relative abundances for more than 5 conformations. The estimation of this maximum number of conformations is intrinsic to the methodology we have used here. PMID:26924916
Brown, Joseph W; Parins-Fukuchi, Caroline; Stull, Gregory W; Vargas, Oscar M; Smith, Stephen A
2017-10-11
Puttick et al. (2017 Proc. R. Soc. B 284 , 20162290 (doi:10.1098/rspb.2016.2290)) performed a simulation study to compare accuracy among methods of inferring phylogeny from discrete morphological characters. They report that a Bayesian implementation of the Mk model (Lewis 2001 Syst. Biol. 50 , 913-925 (doi:10.1080/106351501753462876)) was most accurate (but with low resolution), while a maximum-likelihood (ML) implementation of the same model was least accurate. They conclude by strongly advocating that Bayesian implementations of the Mk model should be the default method of analysis for such data. While we appreciate the authors' attempt to investigate the accuracy of alternative methods of analysis, their conclusion is based on an inappropriate comparison of the ML point estimate, which does not consider confidence, with the Bayesian consensus, which incorporates estimation credibility into the summary tree. Using simulation, we demonstrate that ML and Bayesian estimates are concordant when confidence and credibility are comparably reflected in summary trees, a result expected from statistical theory. We therefore disagree with the conclusions of Puttick et al. and consider their prescription of any default method to be poorly founded. Instead, we recommend caution and thoughtful consideration of the model or method being applied to a morphological dataset. © 2017 The Author(s).
Inferring Phylogenetic Networks Using PhyloNet.
Wen, Dingqiao; Yu, Yun; Zhu, Jiafan; Nakhleh, Luay
2018-07-01
PhyloNet was released in 2008 as a software package for representing and analyzing phylogenetic networks. At the time of its release, the main functionalities in PhyloNet consisted of measures for comparing network topologies and a single heuristic for reconciling gene trees with a species tree. Since then, PhyloNet has grown significantly. The software package now includes a wide array of methods for inferring phylogenetic networks from data sets of unlinked loci while accounting for both reticulation (e.g., hybridization) and incomplete lineage sorting. In particular, PhyloNet now allows for maximum parsimony, maximum likelihood, and Bayesian inference of phylogenetic networks from gene tree estimates. Furthermore, Bayesian inference directly from sequence data (sequence alignments or biallelic markers) is implemented. Maximum parsimony is based on an extension of the "minimizing deep coalescences" criterion to phylogenetic networks, whereas maximum likelihood and Bayesian inference are based on the multispecies network coalescent. All methods allow for multiple individuals per species. As computing the likelihood of a phylogenetic network is computationally hard, PhyloNet allows for evaluation and inference of networks using a pseudolikelihood measure. PhyloNet summarizes the results of the various analyzes and generates phylogenetic networks in the extended Newick format that is readily viewable by existing visualization software.
Molecular Phylogenetics: Mathematical Framework and Unsolved Problems
Xia, Xuhua
Phylogenetic relationship is essential in dating evolutionary events, reconstructing ancestral genes, predicting sites that are important to natural selection, and, ultimately, understanding genomic evolution. Three categories of phylogenetic methods are currently used: the distance-based, the maximum parsimony, and the maximum likelihood method. Here, I present the mathematical framework of these methods and their rationales, provide computational details for each of them, illustrate analytically and numerically the potential biases inherent in these methods, and outline computational challenges and unresolved problems. This is followed by a brief discussion of the Bayesian approach that has been recently used in molecular phylogenetics.
Moslemi, Vahid; Ashoor, Mansour
2017-10-01
One of the major problems associated with parallel hole collimators (PCs) is the trade-off between their resolution and sensitivity. To solve this problem, a novel PC - namely, extended parallel hole collimator (EPC) - was proposed, in which particular trapezoidal denticles were increased upon septa on the side of the detector. In this study, an EPC was designed and its performance was compared with that of two PCs, PC35 and PC41, with a hole size of 1.5 mm and hole lengths of 35 and 41 mm, respectively. The Monte Carlo method was used to calculate the important parameters such as resolution, sensitivity, scattering, and penetration ratio. A Jaszczak phantom was also simulated to evaluate the resolution and contrast of tomographic images, which were produced by the EPC6, PC35, and PC41 using the Monte Carlo N-particle version 5 code, and tomographic images were reconstructed by using maximum likelihood expectation maximization algorithm. Sensitivity of the EPC6 was increased by 20.3% in comparison with that of the PC41 at the identical spatial resolution and full-width at tenth of maximum here. Moreover, the penetration and scattering ratio of the EPC6 was 1.2% less than that of the PC41. The simulated phantom images show that the EPC6 increases contrast-resolution and contrast-to-noise ratio compared with those of PC41 and PC35. When compared with PC41 and PC35, EPC6 improved trade-off between resolution and sensitivity, reduced penetrating and scattering ratios, and produced images with higher quality. EPC6 can be used to increase detectability of more details in nuclear medicine images.
Balzer, Laura B; Zheng, Wenjing; van der Laan, Mark J; Petersen, Maya L
2018-01-01
We often seek to estimate the impact of an exposure naturally occurring or randomly assigned at the cluster-level. For example, the literature on neighborhood determinants of health continues to grow. Likewise, community randomized trials are applied to learn about real-world implementation, sustainability, and population effects of interventions with proven individual-level efficacy. In these settings, individual-level outcomes are correlated due to shared cluster-level factors, including the exposure, as well as social or biological interactions between individuals. To flexibly and efficiently estimate the effect of a cluster-level exposure, we present two targeted maximum likelihood estimators (TMLEs). The first TMLE is developed under a non-parametric causal model, which allows for arbitrary interactions between individuals within a cluster. These interactions include direct transmission of the outcome (i.e. contagion) and influence of one individual's covariates on another's outcome (i.e. covariate interference). The second TMLE is developed under a causal sub-model assuming the cluster-level and individual-specific covariates are sufficient to control for confounding. Simulations compare the alternative estimators and illustrate the potential gains from pairing individual-level risk factors and outcomes during estimation, while avoiding unwarranted assumptions. Our results suggest that estimation under the sub-model can result in bias and misleading inference in an observational setting. Incorporating working assumptions during estimation is more robust than assuming they hold in the underlying causal model. We illustrate our approach with an application to HIV prevention and treatment.
Chen, Qingxia; Ibrahim, Joseph G
2014-07-01
Multiple Imputation, Maximum Likelihood and Fully Bayesian methods are the three most commonly used model-based approaches in missing data problems. Although it is easy to show that when the responses are missing at random (MAR), the complete case analysis is unbiased and efficient, the aforementioned methods are still commonly used in practice for this setting. To examine the performance of and relationships between these three methods in this setting, we derive and investigate small sample and asymptotic expressions of the estimates and standard errors, and fully examine how these estimates are related for the three approaches in the linear regression model when the responses are MAR. We show that when the responses are MAR in the linear model, the estimates of the regression coefficients using these three methods are asymptotically equivalent to the complete case estimates under general conditions. One simulation and a real data set from a liver cancer clinical trial are given to compare the properties of these methods when the responses are MAR.
Murray, Aja Louise; Booth, Tom; Eisner, Manuel; Obsuth, Ingrid; Ribeaud, Denis
2018-05-22
Whether or not importance should be placed on an all-encompassing general factor of psychopathology (or p factor) in classifying, researching, diagnosing, and treating psychiatric disorders depends (among other issues) on the extent to which comorbidity is symptom-general rather than staying largely within the confines of narrower transdiagnostic factors such as internalizing and externalizing. In this study, we compared three methods of estimating p factor strength. We compared omega hierarchical and explained common variance calculated from confirmatory factor analysis (CFA) bifactor models with maximum likelihood (ML) estimation, from exploratory structural equation modeling/exploratory factor analysis models with a bifactor rotation, and from Bayesian structural equation modeling (BSEM) bifactor models. Our simulation results suggested that BSEM with small variance priors on secondary loadings might be the preferred option. However, CFA with ML also performed well provided secondary loadings were modeled. We provide two empirical examples of applying the three methodologies using a normative sample of youth (z-proso, n = 1,286) and a university counseling sample (n = 359).
Dilla, Shintia Ulfa; Andriyana, Yudhie; Sudartianto
2017-03-01
Acid rain causes many bad effects in life. It is formed by two strong acids, sulfuric acid (H2SO4) and nitric acid (HNO3), where sulfuric acid is derived from SO2 and nitric acid from NOx {x=1,2}. The purpose of the research is to find out the influence of So4 and NO3 levels contained in the rain to the acidity (pH) of rainwater. The data are incomplete panel data with two-way error component model. The panel data is a collection of some of the observations that observed from time to time. It is said incomplete if each individual has a different amount of observation. The model used in this research is in the form of random effects model (REM). Minimum variance quadratic unbiased estimation (MIVQUE) is used to estimate the variance error components, while maximum likelihood estimation is used to estimate the parameters. As a result, we obtain the following model: Ŷ* = 0.41276446 - 0.00107302X1 + 0.00215470X2.
Directory of Open Access Journals (Sweden)
Ronald Herrera
2017-12-01
Full Text Available In a town located in a desert area of Northern Chile, gold and copper open-pit mining is carried out involving explosive processes. These processes are associated with increased dust exposure, which might affect children’s respiratory health. Therefore, we aimed to quantify the causal attributable risk of living close to the mines on asthma or allergic rhinoconjunctivitis risk burden in children. Data on the prevalence of respiratory diseases and potential confounders were available from a cross-sectional survey carried out in 2009 among 288 (response: 69 % children living in the community. The proximity of the children’s home addresses to the local gold and copper mine was calculated using geographical positioning systems. We applied targeted maximum likelihood estimation to obtain the causal attributable risk (CAR for asthma, rhinoconjunctivitis and both outcomes combined. Children living more than the first quartile away from the mines were used as the unexposed group. Based on the estimated CAR, a hypothetical intervention in which all children lived at least one quartile away from the copper mine would decrease the risk of rhinoconjunctivitis by 4.7 percentage points (CAR: − 4.7 ; 95 % confidence interval ( 95 % CI: − 8.4 ; − 0.11 ; and 4.2 percentage points (CAR: − 4.2 ; 95 % CI: − 7.9 ; − 0.05 for both outcomes combined. Overall, our results suggest that a hypothetical intervention intended to increase the distance between the place of residence of the highest exposed children would reduce the prevalence of respiratory disease in the community by around four percentage points. This approach could help local policymakers in the development of efficient public health strategies.
Herrera, Ronald; Berger, Ursula; von Ehrenstein, Ondine S; Díaz, Iván; Huber, Stella; Moraga Muñoz, Daniel; Radon, Katja
2017-12-27
In a town located in a desert area of Northern Chile, gold and copper open-pit mining is carried out involving explosive processes. These processes are associated with increased dust exposure, which might affect children's respiratory health. Therefore, we aimed to quantify the causal attributable risk of living close to the mines on asthma or allergic rhinoconjunctivitis risk burden in children. Data on the prevalence of respiratory diseases and potential confounders were available from a cross-sectional survey carried out in 2009 among 288 (response: 69 % ) children living in the community. The proximity of the children's home addresses to the local gold and copper mine was calculated using geographical positioning systems. We applied targeted maximum likelihood estimation to obtain the causal attributable risk (CAR) for asthma, rhinoconjunctivitis and both outcomes combined. Children living more than the first quartile away from the mines were used as the unexposed group. Based on the estimated CAR, a hypothetical intervention in which all children lived at least one quartile away from the copper mine would decrease the risk of rhinoconjunctivitis by 4.7 percentage points (CAR: - 4.7 ; 95 % confidence interval ( 95 % CI): - 8.4 ; - 0.11 ); and 4.2 percentage points (CAR: - 4.2 ; 95 % CI: - 7.9 ; - 0.05 ) for both outcomes combined. Overall, our results suggest that a hypothetical intervention intended to increase the distance between the place of residence of the highest exposed children would reduce the prevalence of respiratory disease in the community by around four percentage points. This approach could help local policymakers in the development of efficient public health strategies.
Etzel, C J; Shete, S; Beasley, T M; Fernandez, J R; Allison, D B; Amos, C I
2003-01-01
Non-normality of the phenotypic distribution can affect power to detect quantitative trait loci in sib pair studies. Previously, we observed that Winsorizing the sib pair phenotypes increased the power of quantitative trait locus (QTL) detection for both Haseman-Elston (HE) least-squares tests [Hum Hered 2002;53:59-67] and maximum likelihood-based variance components (MLVC) analysis [Behav Genet (in press)]. Winsorizing the phenotypes led to a slight increase in type 1 error in H-E tests and a slight decrease in type I error for MLVC analysis. Herein, we considered transforming the sib pair phenotypes using the Box-Cox family of transformations. Data were simulated for normal and non-normal (skewed and kurtic) distributions. Phenotypic values were replaced by Box-Cox transformed values. Twenty thousand replications were performed for three H-E tests of linkage and the likelihood ratio test (LRT), the Wald test and other robust versions based on the MLVC method. We calculated the relative nominal inflation rate as the ratio of observed empirical type 1 error divided by the set alpha level (5, 1 and 0.1% alpha levels). MLVC tests applied to non-normal data had inflated type I errors (rate ratio greater than 1.0), which were controlled best by Box-Cox transformation and to a lesser degree by Winsorizing. For example, for non-transformed, skewed phenotypes (derived from a chi2 distribution with 2 degrees of freedom), the rates of empirical type 1 error with respect to set alpha level=0.01 were 0.80, 4.35 and 7.33 for the original H-E test, LRT and Wald test, respectively. For the same alpha level=0.01, these rates were 1.12, 3.095 and 4.088 after Winsorizing and 0.723, 1.195 and 1.905 after Box-Cox transformation. Winsorizing reduced inflated error rates for the leptokurtic distribution (derived from a Laplace distribution with mean 0 and variance 8). Further, power (adjusted for empirical type 1 error) at the 0.01 alpha level ranged from 4.7 to 17.3% across all tests
Energy Technology Data Exchange (ETDEWEB)
Driscoll, Donald D [Case Western Reserve Univ., Cleveland, OH (United States)
2004-05-01
of a beta-eliminating cut based on a maximum-likelihood characterization described above.
Avtandilashvili, Maia; Brey, Richard; James, Anthony C
2012-07-01
The U.S. Transuranium and Uranium Registries' tissue donors 0202 and 0407 are the two most highly exposed of the 18 registrants who were involved in the 1965 plutonium fire accident at a defense nuclear facility. Material released during the fire was well characterized as "high fired" refractory plutonium dioxide with 0.32-μm mass median diameter. The extensive bioassay data from long-term follow-up of these two cases were used to evaluate the applicability of the Human Respiratory Tract Model presented by International Commission on Radiological Protection in Publication 66 and its revision proposed by Gregoratto et al. in order to account for the observed long-term retention of insoluble material in the lungs. The maximum likelihood method was used to calculate the point estimates of intake and tissue doses and to examine the effect of different lung clearance, blood absorption, and systemic models on the goodness-of-fit and estimated dose values. With appropriate adjustments, Gregoratto et al. particle transport model coupled with the customized blood absorption parameters yielded a credible fit to the bioassay data for both cases and predicted the Case 0202 liver and skeletal activities measured postmortem. PuO2 particles produced by the plutonium fire are extremely insoluble. About 1% of this material is absorbed from the respiratory tract relatively rapidly, at a rate of about 1 to 2 d (half-time about 8 to 16 h). The remainder (99%) is absorbed extremely slowly, at a rate of about 5 × 10(-6) d (half-time about 400 y). When considering this situation, it appears that doses to other body organs are negligible in comparison to those to tissues of the respiratory tract. About 96% of the total committed weighted dose equivalent is contributed by the lungs. Doses absorbed by these workers' lungs were high: 3.2 Gy to AI and 6.5 Gy to LNTH for Case 0202 (18 y post-intake) and 3.2 Gy to AI and 55.5 Gy to LNTH for Case 0407 (43 y post-intake). This evaluation
International Nuclear Information System (INIS)
Reinaldo Gonzalez; Scott R. Reeves; Eric Eslinger
2007-01-01
, with high vertical resolution, could be generated for many wells. This procedure permits to populate any well location with core-scale estimates of P and P and rock types facilitating the application of geostatistical characterization methods. The first step procedure was to discriminate rock types of similar depositional environment and/or reservoir quality (RQ) using a specific clustering technique. The approach implemented utilized a model-based, probabilistic clustering analysis procedure called GAMLS1,2,3,4 (Geologic Analysis via Maximum Likelihood System) which is based on maximum likelihood principles. During clustering, samples (data at each digitized depth from each well) are probabilistically assigned to a previously specified number of clusters with a fractional probability that varies between zero and one
Directory of Open Access Journals (Sweden)
Edwin J. Niklitschek
2016-10-01
Full Text Available Background Mixture models (MM can be used to describe mixed stocks considering three sets of parameters: the total number of contributing sources, their chemical baseline signatures and their mixing proportions. When all nursery sources have been previously identified and sampled for juvenile fish to produce baseline nursery-signatures, mixing proportions are the only unknown set of parameters to be estimated from the mixed-stock data. Otherwise, the number of sources, as well as some/all nursery-signatures may need to be also estimated from the mixed-stock data. Our goal was to assess bias and uncertainty in these MM parameters when estimated using unconditional maximum likelihood approaches (ML-MM, under several incomplete sampling and nursery-signature separation scenarios. Methods We used a comprehensive dataset containing otolith elemental signatures of 301 juvenile Sparus aurata, sampled in three contrasting years (2008, 2010, 2011, from four distinct nursery habitats. (Mediterranean lagoons Artificial nursery-source and mixed-stock datasets were produced considering: five different sampling scenarios where 0–4 lagoons were excluded from the nursery-source dataset and six nursery-signature separation scenarios that simulated data separated 0.5, 1.5, 2.5, 3.5, 4.5 and 5.5 standard deviations among nursery-signature centroids. Bias (BI and uncertainty (SE were computed to assess reliability for each of the three sets of MM parameters. Results Both bias and uncertainty in mixing proportion estimates were low (BI ≤ 0.14, SE ≤ 0.06 when all nursery-sources were sampled but exhibited large variability among cohorts and increased with the number of non-sampled sources up to BI = 0.24 and SE = 0.11. Bias and variability in baseline signature estimates also increased with the number of non-sampled sources, but tended to be less biased, and more uncertain than mixing proportion ones, across all sampling scenarios (BI < 0.13, SE < 0
Darnaude, Audrey M.
2016-01-01
Background Mixture models (MM) can be used to describe mixed stocks considering three sets of parameters: the total number of contributing sources, their chemical baseline signatures and their mixing proportions. When all nursery sources have been previously identified and sampled for juvenile fish to produce baseline nursery-signatures, mixing proportions are the only unknown set of parameters to be estimated from the mixed-stock data. Otherwise, the number of sources, as well as some/all nursery-signatures may need to be also estimated from the mixed-stock data. Our goal was to assess bias and uncertainty in these MM parameters when estimated using unconditional maximum likelihood approaches (ML-MM), under several incomplete sampling and nursery-signature separation scenarios. Methods We used a comprehensive dataset containing otolith elemental signatures of 301 juvenile Sparus aurata, sampled in three contrasting years (2008, 2010, 2011), from four distinct nursery habitats. (Mediterranean lagoons) Artificial nursery-source and mixed-stock datasets were produced considering: five different sampling scenarios where 0–4 lagoons were excluded from the nursery-source dataset and six nursery-signature separation scenarios that simulated data separated 0.5, 1.5, 2.5, 3.5, 4.5 and 5.5 standard deviations among nursery-signature centroids. Bias (BI) and uncertainty (SE) were computed to assess reliability for each of the three sets of MM parameters. Results Both bias and uncertainty in mixing proportion estimates were low (BI ≤ 0.14, SE ≤ 0.06) when all nursery-sources were sampled but exhibited large variability among cohorts and increased with the number of non-sampled sources up to BI = 0.24 and SE = 0.11. Bias and variability in baseline signature estimates also increased with the number of non-sampled sources, but tended to be less biased, and more uncertain than mixing proportion ones, across all sampling scenarios (BI nursery signatures improved reliability
Phylogenetic reconstruction methods: an overview.
De Bruyn, Alexandre; Martin, Darren P; Lefeuvre, Pierre
2014-01-01
Initially designed to infer evolutionary relationships based on morphological and physiological characters, phylogenetic reconstruction methods have greatly benefited from recent developments in molecular biology and sequencing technologies with a number of powerful methods having been developed specifically to infer phylogenies from macromolecular data. This chapter, while presenting an overview of basic concepts and methods used in phylogenetic reconstruction, is primarily intended as a simplified step-by-step guide to the construction of phylogenetic trees from nucleotide sequences using fairly up-to-date maximum likelihood methods implemented in freely available computer programs. While the analysis of chloroplast sequences from various Vanilla species is used as an illustrative example, the techniques covered here are relevant to the comparative analysis of homologous sequences datasets sampled from any group of organisms.
Sen, Sedat
2018-01-01
Recent research has shown that over-extraction of latent classes can be observed in the Bayesian estimation of the mixed Rasch model when the distribution of ability is non-normal. This study examined the effect of non-normal ability distributions on the number of latent classes in the mixed Rasch model when estimated with maximum likelihood…
Owen, Art B
2001-01-01
Empirical likelihood provides inferences whose validity does not depend on specifying a parametric model for the data. Because it uses a likelihood, the method has certain inherent advantages over resampling methods: it uses the data to determine the shape of the confidence regions, and it makes it easy to combined data from multiple sources. It also facilitates incorporating side information, and it simplifies accounting for censored, truncated, or biased sampling.One of the first books published on the subject, Empirical Likelihood offers an in-depth treatment of this method for constructing confidence regions and testing hypotheses. The author applies empirical likelihood to a range of problems, from those as simple as setting a confidence region for a univariate mean under IID sampling, to problems defined through smooth functions of means, regression models, generalized linear models, estimating equations, or kernel smooths, and to sampling with non-identically distributed data. Abundant figures offer vi...
CERN. Geneva
2015-01-01
Most physics results at the LHC end in a likelihood ratio test. This includes discovery and exclusion for searches as well as mass, cross-section, and coupling measurements. The use of Machine Learning (multivariate) algorithms in HEP is mainly restricted to searches, which can be reduced to classification between two fixed distributions: signal vs. background. I will show how we can extend the use of ML classifiers to distributions parameterized by physical quantities like masses and couplings as well as nuisance parameters associated to systematic uncertainties. This allows for one to approximate the likelihood ratio while still using a high dimensional feature vector for the data. Both the MEM and ABC approaches mentioned above aim to provide inference on model parameters (like cross-sections, masses, couplings, etc.). ABC is fundamentally tied Bayesian inference and focuses on the “likelihood free” setting where only a simulator is available and one cannot directly compute the likelihood for the dat...
Likelihood devices in spatial statistics
Zwet, E.W. van
1999-01-01
One of the main themes of this thesis is the application to spatial data of modern semi- and nonparametric methods. Another, closely related theme is maximum likelihood estimation from spatial data. Maximum likelihood estimation is not common practice in spatial statistics. The method of moments
YOUSOFI, SUGOL; POUYANI, ESKANDAR RASTEGAR; HOJATI, VIDA
2015-01-01
We examined intraspecific relationships of the subspecies Pristurus rupestris iranicus from the northern Persian Gulf area (Hormozgan, Bushehr, and Sistan and Baluchestan provinces). Phylogenetic relationships among these samples were estimated based on the mitochondrial cytochrome b gene. We used three methods of phylogenetic tree reconstruction (maximum likelihood, maximum parsimony, and Bayesian inference). The sampled populations were divided into 5 clades but exhibit little genetic diver...
Lehmann, A; Scheffler, Ch; Hermanussen, M
2010-02-01
Recent progress in modelling individual growth has been achieved by combining the principal component analysis and the maximum likelihood principle. This combination models growth even in incomplete sets of data and in data obtained at irregular intervals. We re-analysed late 18th century longitudinal growth of German boys from the boarding school Carlsschule in Stuttgart. The boys, aged 6-23 years, were measured at irregular 3-12 monthly intervals during the period 1771-1793. At the age of 18 years, mean height was 1652 mm, but height variation was large. The shortest boy reached 1474 mm, the tallest 1826 mm. Measured height closely paralleled modelled height, with mean difference of 4 mm, SD 7 mm. Seasonal height variation was found. Low growth rates occurred in spring and high growth rates in summer and autumn. The present study demonstrates that combining the principal component analysis and the maximum likelihood principle enables growth modelling in historic height data also. Copyright (c) 2009 Elsevier GmbH. All rights reserved.
Maximum Likelihood Learning of Conditional MTE Distributions
DEFF Research Database (Denmark)
Langseth, Helge; Nielsen, Thomas Dyhre; Rumí, Rafael
2009-01-01
We describe a procedure for inducing conditional densities within the mixtures of truncated exponentials (MTE) framework. We analyse possible conditional MTE speciﬁcations and propose a model selection scheme, based on the BIC score, for partitioning the domain of the conditioning variables....... Finally, experimental results demonstrate the applicability of the learning procedure as well as the expressive power of the conditional MTE distribution....
Whelan, Simon
2007-10-01
Phylogenetic tree estimation plays a critical role in a wide variety of molecular studies, including molecular systematics, phylogenetics, and comparative genomics. Finding the optimal tree relating a set of sequences using score-based (optimality criterion) methods, such as maximum likelihood and maximum parsimony, may require all possible trees to be considered, which is not feasible even for modest numbers of sequences. In practice, trees are estimated using heuristics that represent a trade-off between topological accuracy and speed. I present a series of novel algorithms suitable for score-based phylogenetic tree reconstruction that demonstrably improve the accuracy of tree estimates while maintaining high computational speeds. The heuristics function by allowing the efficient exploration of large numbers of trees through novel hill-climbing and resampling strategies. These heuristics, and other computational approximations, are implemented for maximum likelihood estimation of trees in the program Leaphy, and its performance is compared to other popular phylogenetic programs. Trees are estimated from 4059 different protein alignments using a selection of phylogenetic programs and the likelihoods of the tree estimates are compared. Trees estimated using Leaphy are found to have equal to or better likelihoods than trees estimated using other phylogenetic programs in 4004 (98.6%) families and provide a unique best tree that no other program found in 1102 (27.1%) families. The improvement is particularly marked for larger families (80 to 100 sequences), where Leaphy finds a unique best tree in 81.7% of families.
EM for phylogenetic topology reconstruction on nonhomogeneous data.
Ibáñez-Marcelo, Esther; Casanellas, Marta
2014-06-17
The reconstruction of the phylogenetic tree topology of four taxa is, still nowadays, one of the main challenges in phylogenetics. Its difficulties lie in considering not too restrictive evolutionary models, and correctly dealing with the long-branch attraction problem. The correct reconstruction of 4-taxon trees is crucial for making quartet-based methods work and being able to recover large phylogenies. We adapt the well known expectation-maximization algorithm to evolutionary Markov models on phylogenetic 4-taxon trees. We then use this algorithm to estimate the substitution parameters, compute the corresponding likelihood, and to infer the most likely quartet. In this paper we consider an expectation-maximization method for maximizing the likelihood of (time nonhomogeneous) evolutionary Markov models on trees. We study its success on reconstructing 4-taxon topologies and its performance as input method in quartet-based phylogenetic reconstruction methods such as QFIT and QuartetSuite. Our results show that the method proposed here outperforms neighbor-joining and the usual (time-homogeneous continuous-time) maximum likelihood methods on 4-leaved trees with among-lineage instantaneous rate heterogeneity, and perform similarly to usual continuous-time maximum-likelihood when data satisfies the assumptions of both methods. The method presented in this paper is well suited for reconstructing the topology of any number of taxa via quartet-based methods and is highly accurate, specially regarding largely divergent trees and time nonhomogeneous data.
A comparison of maximum entropy and maximum likelihood estimation
Oude Lansink, A.G.J.M.
1999-01-01
Gegevens betreffende het ondernemerschap op Nederlandse akkerbouwbedrijven zijn in 2 benaderingsmethodes verwerkt, welke onderling op voorspellende nauwkeurigheid en op prijs-elasticiteit zijn vergeleken
Balzer, Laura; Staples, Patrick; Onnela, Jukka-Pekka; DeGruttola, Victor
2017-04-01
Several cluster-randomized trials are underway to investigate the implementation and effectiveness of a universal test-and-treat strategy on the HIV epidemic in sub-Saharan Africa. We consider nesting studies of pre-exposure prophylaxis within these trials. Pre-exposure prophylaxis is a general strategy where high-risk HIV- persons take antiretrovirals daily to reduce their risk of infection from exposure to HIV. We address how to target pre-exposure prophylaxis to high-risk groups and how to maximize power to detect the individual and combined effects of universal test-and-treat and pre-exposure prophylaxis strategies. We simulated 1000 trials, each consisting of 32 villages with 200 individuals per village. At baseline, we randomized the universal test-and-treat strategy. Then, after 3 years of follow-up, we considered four strategies for targeting pre-exposure prophylaxis: (1) all HIV- individuals who self-identify as high risk, (2) all HIV- individuals who are identified by their HIV+ partner (serodiscordant couples), (3) highly connected HIV- individuals, and (4) the HIV- contacts of a newly diagnosed HIV+ individual (a ring-based strategy). We explored two possible trial designs, and all villages were followed for a total of 7 years. For each village in a trial, we used a stochastic block model to generate bipartite (male-female) networks and simulated an agent-based epidemic process on these networks. We estimated the individual and combined intervention effects with a novel targeted maximum likelihood estimator, which used cross-validation to data-adaptively select from a pre-specified library the candidate estimator that maximized the efficiency of the analysis. The universal test-and-treat strategy reduced the 3-year cumulative HIV incidence by 4.0% on average. The impact of each pre-exposure prophylaxis strategy on the 4-year cumulative HIV incidence varied by the coverage of the universal test-and-treat strategy with lower coverage resulting in a larger
Directory of Open Access Journals (Sweden)
Yunfeng Shan
2008-01-01
Full Text Available Genomes and genes diversify during evolution; however, it is unclear to what extent genes still retain the relationship among species. Model species for molecular phylogenetic studies include yeasts and viruses whose genomes were sequenced as well as plants that have the fossil-supported true phylogenetic trees available. In this study, we generated single gene trees of seven yeast species as well as single gene trees of nine baculovirus species using all the orthologous genes among the species compared. Homologous genes among seven known plants were used for validation of the ﬁnding. Four algorithms—maximum parsimony (MP, minimum evolution (ME, maximum likelihood (ML, and neighbor-joining (NJ—were used. Trees were reconstructed before and after weighting the DNA and protein sequence lengths among genes. Rarely a gene can always generate the “true tree” by all the four algorithms. However, the most frequent gene tree, termed “maximum gene-support tree” (MGS tree, or WMGS tree for the weighted one, in yeasts, baculoviruses, or plants was consistently found to be the “true tree” among the species. The results provide insights into the overall degree of divergence of orthologous genes of the genomes analyzed and suggest the following: 1 The true tree relationship among the species studied is still maintained by the largest group of orthologous genes; 2 There are usually more orthologous genes with higher similarities between genetically closer species than between genetically more distant ones; and 3 The maximum gene-support tree reﬂects the phylogenetic relationship among species in comparison.
Phylogenetic inference with weighted codon evolutionary distances.
Criscuolo, Alexis; Michel, Christian J
2009-04-01
We develop a new approach to estimate a matrix of pairwise evolutionary distances from a codon-based alignment based on a codon evolutionary model. The method first computes a standard distance matrix for each of the three codon positions. Then these three distance matrices are weighted according to an estimate of the global evolutionary rate of each codon position and averaged into a unique distance matrix. Using a large set of both real and simulated codon-based alignments of nucleotide sequences, we show that this approach leads to distance matrices that have a significantly better treelikeness compared to those obtained by standard nucleotide evolutionary distances. We also propose an alternative weighting to eliminate the part of the noise often associated with some codon positions, particularly the third position, which is known to induce a fast evolutionary rate. Simulation results show that fast distance-based tree reconstruction algorithms on distance matrices based on this codon position weighting can lead to phylogenetic trees that are at least as accurate as, if not better, than those inferred by maximum likelihood. Finally, a well-known multigene dataset composed of eight yeast species and 106 codon-based alignments is reanalyzed and shows that our codon evolutionary distances allow building a phylogenetic tree which is similar to those obtained by non-distance-based methods (e.g., maximum parsimony and maximum likelihood) and also significantly improved compared to standard nucleotide evolutionary distance estimates.
A gateway for phylogenetic analysis powered by grid computing featuring GARLI 2.0.
Bazinet, Adam L; Zwickl, Derrick J; Cummings, Michael P
2014-09-01
We introduce molecularevolution.org, a publicly available gateway for high-throughput, maximum-likelihood phylogenetic analysis powered by grid computing. The gateway features a garli 2.0 web service that enables a user to quickly and easily submit thousands of maximum likelihood tree searches or bootstrap searches that are executed in parallel on distributed computing resources. The garli web service allows one to easily specify partitioned substitution models using a graphical interface, and it performs sophisticated post-processing of phylogenetic results. Although the garli web service has been used by the research community for over three years, here we formally announce the availability of the service, describe its capabilities, highlight new features and recent improvements, and provide details about how the grid system efficiently delivers high-quality phylogenetic results. © The Author(s) 2014. Published by Oxford University Press, on behalf of the Society of Systematic Biologists.
Rearrangement moves on rooted phylogenetic networks.
Gambette, Philippe; van Iersel, Leo; Jones, Mark; Lafond, Manuel; Pardi, Fabio; Scornavacca, Celine
2017-08-01
Phylogenetic tree reconstruction is usually done by local search heuristics that explore the space of the possible tree topologies via simple rearrangements of their structure. Tree rearrangement heuristics have been used in combination with practically all optimization criteria in use, from maximum likelihood and parsimony to distance-based principles, and in a Bayesian context. Their basic components are rearrangement moves that specify all possible ways of generating alternative phylogenies from a given one, and whose fundamental property is to be able to transform, by repeated application, any phylogeny into any other phylogeny. Despite their long tradition in tree-based phylogenetics, very little research has gone into studying similar rearrangement operations for phylogenetic network-that is, phylogenies explicitly representing scenarios that include reticulate events such as hybridization, horizontal gene transfer, population admixture, and recombination. To fill this gap, we propose "horizontal" moves that ensure that every network of a certain complexity can be reached from any other network of the same complexity, and "vertical" moves that ensure reachability between networks of different complexities. When applied to phylogenetic trees, our horizontal moves-named rNNI and rSPR-reduce to the best-known moves on rooted phylogenetic trees, nearest-neighbor interchange and rooted subtree pruning and regrafting. Besides a number of reachability results-separating the contributions of horizontal and vertical moves-we prove that rNNI moves are local versions of rSPR moves, and provide bounds on the sizes of the rNNI neighborhoods. The paper focuses on the most biologically meaningful versions of phylogenetic networks, where edges are oriented and reticulation events clearly identified. Moreover, our rearrangement moves are robust to the fact that networks with higher complexity usually allow a better fit with the data. Our goal is to provide a solid basis for
Rearrangement moves on rooted phylogenetic networks.
Directory of Open Access Journals (Sweden)
Philippe Gambette
2017-08-01
Full Text Available Phylogenetic tree reconstruction is usually done by local search heuristics that explore the space of the possible tree topologies via simple rearrangements of their structure. Tree rearrangement heuristics have been used in combination with practically all optimization criteria in use, from maximum likelihood and parsimony to distance-based principles, and in a Bayesian context. Their basic components are rearrangement moves that specify all possible ways of generating alternative phylogenies from a given one, and whose fundamental property is to be able to transform, by repeated application, any phylogeny into any other phylogeny. Despite their long tradition in tree-based phylogenetics, very little research has gone into studying similar rearrangement operations for phylogenetic network-that is, phylogenies explicitly representing scenarios that include reticulate events such as hybridization, horizontal gene transfer, population admixture, and recombination. To fill this gap, we propose "horizontal" moves that ensure that every network of a certain complexity can be reached from any other network of the same complexity, and "vertical" moves that ensure reachability between networks of different complexities. When applied to phylogenetic trees, our horizontal moves-named rNNI and rSPR-reduce to the best-known moves on rooted phylogenetic trees, nearest-neighbor interchange and rooted subtree pruning and regrafting. Besides a number of reachability results-separating the contributions of horizontal and vertical moves-we prove that rNNI moves are local versions of rSPR moves, and provide bounds on the sizes of the rNNI neighborhoods. The paper focuses on the most biologically meaningful versions of phylogenetic networks, where edges are oriented and reticulation events clearly identified. Moreover, our rearrangement moves are robust to the fact that networks with higher complexity usually allow a better fit with the data. Our goal is to provide
Robustness of ancestral sequence reconstruction to phylogenetic uncertainty.
Hanson-Smith, Victor; Kolaczkowski, Bryan; Thornton, Joseph W
2010-09-01
Ancestral sequence reconstruction (ASR) is widely used to formulate and test hypotheses about the sequences, functions, and structures of ancient genes. Ancestral sequences are usually inferred from an alignment of extant sequences using a maximum likelihood (ML) phylogenetic algorithm, which calculates the most likely ancestral sequence assuming a probabilistic model of sequence evolution and a specific phylogeny--typically the tree with the ML. The true phylogeny is seldom known with certainty, however. ML methods ignore this uncertainty, whereas Bayesian methods incorporate it by integrating the likelihood of each ancestral state over a distribution of possible trees. It is not known whether Bayesian approaches to phylogenetic uncertainty improve the accuracy of inferred ancestral sequences. Here, we use simulation-based experiments under both simplified and empirically derived conditions to compare the accuracy of ASR carried out using ML and Bayesian approaches. We show that incorporating phylogenetic uncertainty by integrating over topologies very rarely changes the inferred ancestral state and does not improve the accuracy of the reconstructed ancestral sequence. Ancestral state reconstructions are robust to uncertainty about the underlying tree because the conditions that produce phylogenetic uncertainty also make the ancestral state identical across plausible trees; conversely, the conditions under which different phylogenies yield different inferred ancestral states produce little or no ambiguity about the true phylogeny. Our results suggest that ML can produce accurate ASRs, even in the face of phylogenetic uncertainty. Using Bayesian integration to incorporate this uncertainty is neither necessary nor beneficial.
One tree to link them all: a phylogenetic dataset for the European tetrapoda.
Roquet, Cristina; Lavergne, Sébastien; Thuiller, Wilfried
2014-08-08
Since the ever-increasing availability of phylogenetic informative data, the last decade has seen an upsurge of ecological studies incorporating information on evolutionary relationships among species. However, detailed species-level phylogenies are still lacking for many large groups and regions, which are necessary for comprehensive large-scale eco-phylogenetic analyses. Here, we provide a dataset of 100 dated phylogenetic trees for all European tetrapods based on a mixture of supermatrix and supertree approaches. Phylogenetic inference was performed separately for each of the main Tetrapoda groups of Europe except mammals (i.e. amphibians, birds, squamates and turtles) by means of maximum likelihood (ML) analyses of supermatrix applying a tree constraint at the family (amphibians and squamates) or order (birds and turtles) levels based on consensus knowledge. For each group, we inferred 100 ML trees to be able to provide a phylogenetic dataset that accounts for phylogenetic uncertainty, and assessed node support with bootstrap analyses. Each tree was dated using penalized-likelihood and fossil calibration. The trees obtained were well-supported by existing knowledge and previous phylogenetic studies. For mammals, we modified the most complete supertree dataset available on the literature to include a recent update of the Carnivora clade. As a final step, we merged the phylogenetic trees of all groups to obtain a set of 100 phylogenetic trees for all European Tetrapoda species for which data was available (91%). We provide this phylogenetic dataset (100 chronograms) for the purpose of comparative analyses, macro-ecological or community ecology studies aiming to incorporate phylogenetic information while accounting for phylogenetic uncertainty.
Baños, Hector; Bushek, Nathaniel; Davidson, Ruth; Gross, Elizabeth; Harris, Pamela E.; Krone, Robert; Long, Colby; Stewart, Allen; Walker, Robert
2016-01-01
We introduce the package PhylogeneticTrees for Macaulay2 which allows users to compute phylogenetic invariants for group-based tree models. We provide some background information on phylogenetic algebraic geometry and show how the package PhylogeneticTrees can be used to calculate a generating set for a phylogenetic ideal as well as a lower bound for its dimension. Finally, we show how methods within the package can be used to compute a generating set for the join of any two ideals.
Evaluation of properties over phylogenetic trees using stochastic logics.
Requeno, José Ignacio; Colom, José Manuel
2016-06-14
Model checking has been recently introduced as an integrated framework for extracting information of the phylogenetic trees using temporal logics as a querying language, an extension of modal logics that imposes restrictions of a boolean formula along a path of events. The phylogenetic tree is considered a transition system modeling the evolution as a sequence of genomic mutations (we understand mutation as different ways that DNA can be changed), while this kind of logics are suitable for traversing it in a strict and exhaustive way. Given a biological property that we desire to inspect over the phylogeny, the verifier returns true if the specification is satisfied or a counterexample that falsifies it. However, this approach has been only considered over qualitative aspects of the phylogeny. In this paper, we repair the limitations of the previous framework for including and handling quantitative information such as explicit time or probability. To this end, we apply current probabilistic continuous-time extensions of model checking to phylogenetics. We reinterpret a catalog of qualitative properties in a numerical way, and we also present new properties that couldn't be analyzed before. For instance, we obtain the likelihood of a tree topology according to a mutation model. As case of study, we analyze several phylogenies in order to obtain the maximum likelihood with the model checking tool PRISM. In addition, we have adapted the software for optimizing the computation of maximum likelihoods. We have shown that probabilistic model checking is a competitive framework for describing and analyzing quantitative properties over phylogenetic trees. This formalism adds soundness and readability to the definition of models and specifications. Besides, the existence of model checking tools hides the underlying technology, omitting the extension, upgrade, debugging and maintenance of a software tool to the biologists. A set of benchmarks justify the feasibility of our
van der Kuyl, Antoinette C.; Ph Ballasina, Donato L.; Dekker, John T.; Maas, Jolanda; Willemsen, Ronald E.; Goudsmit, Jaap
2002-01-01
To test phylogenetic relationships within the genus Testudo (Testudines: Testudinidae), we have sequenced a fragment of the mitochondrial (mt) 12S rRNA gene of 98 tortoise specimens belonging to the genera Testudo, Indotestudo, and Geochelone. Maximum likelihood and neighbor-joining methods identify
Phylogenetic evidence for cladogenetic polyploidization in land plants.
Zhan, Shing H; Drori, Michal; Goldberg, Emma E; Otto, Sarah P; Mayrose, Itay
2016-07-01
Polyploidization is a common and recurring phenomenon in plants and is often thought to be a mechanism of "instant speciation". Whether polyploidization is associated with the formation of new species (cladogenesis) or simply occurs over time within a lineage (anagenesis), however, has never been assessed systematically. We tested this hypothesis using phylogenetic and karyotypic information from 235 plant genera (mostly angiosperms). We first constructed a large database of combined sequence and chromosome number data sets using an automated procedure. We then applied likelihood models (ClaSSE) that estimate the degree of synchronization between polyploidization and speciation events in maximum likelihood and Bayesian frameworks. Our maximum likelihood analysis indicated that 35 genera supported a model that includes cladogenetic transitions over a model with only anagenetic transitions, whereas three genera supported a model that incorporates anagenetic transitions over one with only cladogenetic transitions. Furthermore, the Bayesian analysis supported a preponderance of cladogenetic change in four genera but did not support a preponderance of anagenetic change in any genus. Overall, these phylogenetic analyses provide the first broad confirmation that polyploidization is temporally associated with speciation events, suggesting that it is indeed a major speciation mechanism in plants, at least in some genera. © 2016 Botanical Society of America.
PTree: pattern-based, stochastic search for maximum parsimony phylogenies
Directory of Open Access Journals (Sweden)
Ivan Gregor
2013-06-01
Full Text Available Phylogenetic reconstruction is vital to analyzing the evolutionary relationship of genes within and across populations of different species. Nowadays, with next generation sequencing technologies producing sets comprising thousands of sequences, robust identification of the tree topology, which is optimal according to standard criteria such as maximum parsimony, maximum likelihood or posterior probability, with phylogenetic inference methods is a computationally very demanding task. Here, we describe a stochastic search method for a maximum parsimony tree, implemented in a software package we named PTree. Our method is based on a new pattern-based technique that enables us to infer intermediate sequences efficiently where the incorporation of these sequences in the current tree topology yields a phylogenetic tree with a lower cost. Evaluation across multiple datasets showed that our method is comparable to the algorithms implemented in PAUP* or TNT, which are widely used by the bioinformatics community, in terms of topological accuracy and runtime. We show that our method can process large-scale datasets of 1,000–8,000 sequences. We believe that our novel pattern-based method enriches the current set of tools and methods for phylogenetic tree inference. The software is available under: http://algbio.cs.uni-duesseldorf.de/webapps/wa-download/.
PTree: pattern-based, stochastic search for maximum parsimony phylogenies.
Gregor, Ivan; Steinbrück, Lars; McHardy, Alice C
2013-01-01
Phylogenetic reconstruction is vital to analyzing the evolutionary relationship of genes within and across populations of different species. Nowadays, with next generation sequencing technologies producing sets comprising thousands of sequences, robust identification of the tree topology, which is optimal according to standard criteria such as maximum parsimony, maximum likelihood or posterior probability, with phylogenetic inference methods is a computationally very demanding task. Here, we describe a stochastic search method for a maximum parsimony tree, implemented in a software package we named PTree. Our method is based on a new pattern-based technique that enables us to infer intermediate sequences efficiently where the incorporation of these sequences in the current tree topology yields a phylogenetic tree with a lower cost. Evaluation across multiple datasets showed that our method is comparable to the algorithms implemented in PAUP* or TNT, which are widely used by the bioinformatics community, in terms of topological accuracy and runtime. We show that our method can process large-scale datasets of 1,000-8,000 sequences. We believe that our novel pattern-based method enriches the current set of tools and methods for phylogenetic tree inference. The software is available under: http://algbio.cs.uni-duesseldorf.de/webapps/wa-download/.
A format for phylogenetic placements.
Directory of Open Access Journals (Sweden)
Frederick A Matsen
Full Text Available We have developed a unified format for phylogenetic placements, that is, mappings of environmental sequence data (e.g., short reads into a phylogenetic tree. We are motivated to do so by the growing number of tools for computing and post-processing phylogenetic placements, and the lack of an established standard for storing them. The format is lightweight, versatile, extensible, and is based on the JSON format, which can be parsed by most modern programming languages. Our format is already implemented in several tools for computing and post-processing parsimony- and likelihood-based phylogenetic placements and has worked well in practice. We believe that establishing a standard format for analyzing read placements at this early stage will lead to a more efficient development of powerful and portable post-analysis tools for the growing applications of phylogenetic placement.
A Distance Measure for Genome Phylogenetic Analysis
Cao, Minh Duc; Allison, Lloyd; Dix, Trevor
Phylogenetic analyses of species based on single genes or parts of the genomes are often inconsistent because of factors such as variable rates of evolution and horizontal gene transfer. The availability of more and more sequenced genomes allows phylogeny construction from complete genomes that is less sensitive to such inconsistency. For such long sequences, construction methods like maximum parsimony and maximum likelihood are often not possible due to their intensive computational requirement. Another class of tree construction methods, namely distance-based methods, require a measure of distances between any two genomes. Some measures such as evolutionary edit distance of gene order and gene content are computational expensive or do not perform well when the gene content of the organisms are similar. This study presents an information theoretic measure of genetic distances between genomes based on the biological compression algorithm expert model. We demonstrate that our distance measure can be applied to reconstruct the consensus phylogenetic tree of a number of Plasmodium parasites from their genomes, the statistical bias of which would mislead conventional analysis methods. Our approach is also used to successfully construct a plausible evolutionary tree for the γ-Proteobacteria group whose genomes are known to contain many horizontally transferred genes.
Accurate phylogenetic tree reconstruction from quartets: a heuristic approach.
Reaz, Rezwana; Bayzid, Md Shamsuzzoha; Rahman, M Sohel
2014-01-01
Supertree methods construct trees on a set of taxa (species) combining many smaller trees on the overlapping subsets of the entire set of taxa. A 'quartet' is an unrooted tree over 4 taxa, hence the quartet-based supertree methods combine many 4-taxon unrooted trees into a single and coherent tree over the complete set of taxa. Quartet-based phylogeny reconstruction methods have been receiving considerable attentions in the recent years. An accurate and efficient quartet-based method might be competitive with the current best phylogenetic tree reconstruction methods (such as maximum likelihood or Bayesian MCMC analyses), without being as computationally intensive. In this paper, we present a novel and highly accurate quartet-based phylogenetic tree reconstruction method. We performed an extensive experimental study to evaluate the accuracy and scalability of our approach on both simulated and biological datasets.
International Nuclear Information System (INIS)
Wall, M.J.W.
1992-01-01
The notion of open-quotes probabilityclose quotes is generalized to that of open-quotes likelihood,close quotes and a natural logical structure is shown to exist for any physical theory which predicts likelihoods. Two physically based axioms are given for this logical structure to form an orthomodular poset, with an order-determining set of states. The results strengthen the basis of the quantum logic approach to axiomatic quantum theory. 25 refs
Bashalkhanov, S I; Konstantinov, Iu M; Verbitskiĭ, D S; Kobzev, V F
2003-10-01
To reconstruct the systematic relationships of larch Larix sukaczewii, we used the chloroplast trnK intron sequences of L. decidua, L. sukaczewii, L. sibirica, L. czekanovskii, and L. gmelinii. Analysis of phylogenetic trees constructed using the maximum parsimony and maximum likelihood methods showed a clear divergence of the trnK intron sequences between L. sukaczewii and L. sibirica. This divergence reaches intraspecific level, which supports a previously published hypothesis on the taxonomic isolation of L. sukaczewii.
Maximum likely scale estimation
DEFF Research Database (Denmark)
Loog, Marco; Pedersen, Kim Steenstrup; Markussen, Bo
2005-01-01
A maximum likelihood local scale estimation principle is presented. An actual implementation of the estimation principle uses second order moments of multiple measurements at a fixed location in the image. These measurements consist of Gaussian derivatives possibly taken at several scales and/or ...
Jansen, Robert K; Kaittanis, Charalambos; Saski, Christopher; Lee, Seung-Bum; Tomkins, Jeffrey; Alverson, Andrew J; Daniell, Henry
2006-04-09
The Vitaceae (grape) is an economically important family of angiosperms whose phylogenetic placement is currently unresolved. Recent phylogenetic analyses based on one to several genes have suggested several alternative placements of this family, including sister to Caryophyllales, asterids, Saxifragales, Dilleniaceae or to rest of rosids, though support for these different results has been weak. There has been a recent interest in using complete chloroplast genome sequences for resolving phylogenetic relationships among angiosperms. These studies have clarified relationships among several major lineages but they have also emphasized the importance of taxon sampling and the effects of different phylogenetic methods for obtaining accurate phylogenies. We sequenced the complete chloroplast genome of Vitis vinifera and used these data to assess relationships among 27 angiosperms, including nine taxa of rosids. The Vitis vinifera chloroplast genome is 160,928 bp in length, including a pair of inverted repeats of 26,358 bp that are separated by small and large single copy regions of 19,065 bp and 89,147 bp, respectively. The gene content and order of Vitis is identical to many other unrearranged angiosperm chloroplast genomes, including tobacco. Phylogenetic analyses using maximum parsimony and maximum likelihood were performed on DNA sequences of 61 protein-coding genes for two datasets with 28 or 29 taxa, including eight or nine taxa from four of the seven currently recognized major clades of rosids. Parsimony and likelihood phylogenies of both data sets provide strong support for the placement of Vitaceae as sister to the remaining rosids. However, the position of the Myrtales and support for the monophyly of the eurosid I clade differs between the two data sets and the two methods of analysis. In parsimony analyses, the inclusion of Gossypium is necessary to obtain trees that support the monophyly of the eurosid I clade. However, maximum likelihood analyses place
Directory of Open Access Journals (Sweden)
Alverson Andrew J
2006-04-01
Full Text Available Abstract Background The Vitaceae (grape is an economically important family of angiosperms whose phylogenetic placement is currently unresolved. Recent phylogenetic analyses based on one to several genes have suggested several alternative placements of this family, including sister to Caryophyllales, asterids, Saxifragales, Dilleniaceae or to rest of rosids, though support for these different results has been weak. There has been a recent interest in using complete chloroplast genome sequences for resolving phylogenetic relationships among angiosperms. These studies have clarified relationships among several major lineages but they have also emphasized the importance of taxon sampling and the effects of different phylogenetic methods for obtaining accurate phylogenies. We sequenced the complete chloroplast genome of Vitis vinifera and used these data to assess relationships among 27 angiosperms, including nine taxa of rosids. Results The Vitis vinifera chloroplast genome is 160,928 bp in length, including a pair of inverted repeats of 26,358 bp that are separated by small and large single copy regions of 19,065 bp and 89,147 bp, respectively. The gene content and order of Vitis is identical to many other unrearranged angiosperm chloroplast genomes, including tobacco. Phylogenetic analyses using maximum parsimony and maximum likelihood were performed on DNA sequences of 61 protein-coding genes for two datasets with 28 or 29 taxa, including eight or nine taxa from four of the seven currently recognized major clades of rosids. Parsimony and likelihood phylogenies of both data sets provide strong support for the placement of Vitaceae as sister to the remaining rosids. However, the position of the Myrtales and support for the monophyly of the eurosid I clade differs between the two data sets and the two methods of analysis. In parsimony analyses, the inclusion of Gossypium is necessary to obtain trees that support the monophyly of the eurosid I clade
Behavior of the maximum likelihood in quantum state tomography
Scholten, Travis L.; Blume-Kohout, Robin
2018-02-01
Quantum state tomography on a d-dimensional system demands resources that grow rapidly with d. They may be reduced by using model selection to tailor the number of parameters in the model (i.e., the size of the density matrix). Most model selection methods typically rely on a test statistic and a null theory that describes its behavior when two models are equally good. Here, we consider the loglikelihood ratio. Because of the positivity constraint ρ ≥ 0, quantum state space does not generally satisfy local asymptotic normality (LAN), meaning the classical null theory for the loglikelihood ratio (the Wilks theorem) should not be used. Thus, understanding and quantifying how positivity affects the null behavior of this test statistic is necessary for its use in model selection for state tomography. We define a new generalization of LAN, metric-projected LAN, show that quantum state space satisfies it, and derive a replacement for the Wilks theorem. In addition to enabling reliable model selection, our results shed more light on the qualitative effects of the positivity constraint on state tomography.
Vector Antenna and Maximum Likelihood Imaging for Radio Astronomy
2016-03-05
398, 1994. [21] A. Nehorai, K. C. Ho, and B. T. G. Tan , “Minimum- 14 noise-variance beamformer with an electromagnetic vector sensor,” IEEE...G. Eslinger, A. Nicholas , and C. Pong, “The MicroMAS CubeSat Mission,” AGU Fall Meet. Abstr., vol. -1, p. 2162, Dec. 2012. [39] W. Blackwell, G
Bayesian and maximum likelihood estimation of genetic maps
DEFF Research Database (Denmark)
York, Thomas L.; Durrett, Richard T.; Tanksley, Steven
2005-01-01
There has recently been increased interest in the use of Markov Chain Monte Carlo (MCMC)-based Bayesian methods for estimating genetic maps. The advantage of these methods is that they can deal accurately with missing data and genotyping errors. Here we present an extension of the previous methods...... of genotyping errors. A similar advantage of the Bayesian method was not observed for missing data. We also re-analyse a recently published set of data from the eggplant and show that the use of the MCMC-based method leads to smaller estimates of genetic distances....
Behavior of the maximum likelihood in quantum state tomography
Energy Technology Data Exchange (ETDEWEB)
Blume-Kohout, Robin J [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Univ. of New Mexico, Albuquerque, NM (United States); Scholten, Travis L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Univ. of New Mexico, Albuquerque, NM (United States)
2018-02-22
Quantum state tomography on a d-dimensional system demands resources that grow rapidly with d. They may be reduced by using model selection to tailor the number of parameters in the model (i.e., the size of the density matrix). Most model selection methods typically rely on a test statistic and a null theory that describes its behavior when two models are equally good. Here, we consider the loglikelihood ratio. Because of the positivity constraint ρ ≥ 0, quantum state space does not generally satisfy local asymptotic normality (LAN), meaning the classical null theory for the loglikelihood ratio (the Wilks theorem) should not be used. Thus, understanding and quantifying how positivity affects the null behavior of this test statistic is necessary for its use in model selection for state tomography. We define a new generalization of LAN, metric-projected LAN, show that quantum state space satisfies it, and derive a replacement for the Wilks theorem. In addition to enabling reliable model selection, our results shed more light on the qualitative effects of the positivity constraint on state tomography.
Zhou, Tai-Cheng; Sha, Tao; Irwin, David M; Zhang, Ya-Ping
2015-01-01
Pavo cristatus, known as the Indian peafowl, is endemic to India and Sri Lanka and has been domesticated for its ornamental and food value. However, its phylogenetic status is still debated. Here, to clarify the phylogenetic status of P. cristatus within Phasianidae, we analyzed its mitochondrial genome (mtDNA). The complete mitochondrial DNA (mtDNA) genome was determined using 34 pairs of primers. Our data show that the mtDNA genome of P. cristatus is 16,686 bp in length. Molecular phylogenetic analyses of P. cristatus was performed along with 22 complete mtDNA genomes belonging to other species in Phasianidae using Bayesian and maximum likelihood methods, where Aythya americana and Anas platyrhynchos were used as outgroups. Our results show that P. critatus has its closest genetic affinity with Pavo muticus and belongs to clade that contains Gallus, Bambusicola and Francolinus.
Reconstructible phylogenetic networks: do not distinguish the indistinguishable.
Pardi, Fabio; Scornavacca, Celine
2015-04-01
Phylogenetic networks represent the evolution of organisms that have undergone reticulate events, such as recombination, hybrid speciation or lateral gene transfer. An important way to interpret a phylogenetic network is in terms of the trees it displays, which represent all the possible histories of the characters carried by the organisms in the network. Interestingly, however, different networks may display exactly the same set of trees, an observation that poses a problem for network reconstruction: from the perspective of many inference methods such networks are "indistinguishable". This is true for all methods that evaluate a phylogenetic network solely on the basis of how well the displayed trees fit the available data, including all methods based on input data consisting of clades, triples, quartets, or trees with any number of taxa, and also sequence-based approaches such as popular formalisations of maximum parsimony and maximum likelihood for networks. This identifiability problem is partially solved by accounting for branch lengths, although this merely reduces the frequency of the problem. Here we propose that network inference methods should only attempt to reconstruct what they can uniquely identify. To this end, we introduce a novel definition of what constitutes a uniquely reconstructible network. For any given set of indistinguishable networks, we define a canonical network that, under mild assumptions, is unique and thus representative of the entire set. Given data that underwent reticulate evolution, only the canonical form of the underlying phylogenetic network can be uniquely reconstructed. While on the methodological side this will imply a drastic reduction of the solution space in network inference, for the study of reticulate evolution this is a fundamental limitation that will require an important change of perspective when interpreting phylogenetic networks.
Reconstructible phylogenetic networks: do not distinguish the indistinguishable.
Directory of Open Access Journals (Sweden)
Fabio Pardi
2015-04-01
Full Text Available Phylogenetic networks represent the evolution of organisms that have undergone reticulate events, such as recombination, hybrid speciation or lateral gene transfer. An important way to interpret a phylogenetic network is in terms of the trees it displays, which represent all the possible histories of the characters carried by the organisms in the network. Interestingly, however, different networks may display exactly the same set of trees, an observation that poses a problem for network reconstruction: from the perspective of many inference methods such networks are "indistinguishable". This is true for all methods that evaluate a phylogenetic network solely on the basis of how well the displayed trees fit the available data, including all methods based on input data consisting of clades, triples, quartets, or trees with any number of taxa, and also sequence-based approaches such as popular formalisations of maximum parsimony and maximum likelihood for networks. This identifiability problem is partially solved by accounting for branch lengths, although this merely reduces the frequency of the problem. Here we propose that network inference methods should only attempt to reconstruct what they can uniquely identify. To this end, we introduce a novel definition of what constitutes a uniquely reconstructible network. For any given set of indistinguishable networks, we define a canonical network that, under mild assumptions, is unique and thus representative of the entire set. Given data that underwent reticulate evolution, only the canonical form of the underlying phylogenetic network can be uniquely reconstructed. While on the methodological side this will imply a drastic reduction of the solution space in network inference, for the study of reticulate evolution this is a fundamental limitation that will require an important change of perspective when interpreting phylogenetic networks.
Peyre, Hugo; Leplège, Alain; Coste, Joël
2011-03-01
Missing items are common in quality of life (QoL) questionnaires and present a challenge for research in this field. It remains unclear which of the various methods proposed to deal with missing data performs best in this context. We compared personal mean score, full information maximum likelihood, multiple imputation, and hot deck techniques using various realistic simulation scenarios of item missingness in QoL questionnaires constructed within the framework of classical test theory. Samples of 300 and 1,000 subjects were randomly drawn from the 2003 INSEE Decennial Health Survey (of 23,018 subjects representative of the French population and having completed the SF-36) and various patterns of missing data were generated according to three different item non-response rates (3, 6, and 9%) and three types of missing data (Little and Rubin's "missing completely at random," "missing at random," and "missing not at random"). The missing data methods were evaluated in terms of accuracy and precision for the analysis of one descriptive and one association parameter for three different scales of the SF-36. For all item non-response rates and types of missing data, multiple imputation and full information maximum likelihood appeared superior to the personal mean score and especially to hot deck in terms of accuracy and precision; however, the use of personal mean score was associated with insignificant bias (relative bias personal mean score appears nonetheless appropriate for dealing with items missing from completed SF-36 questionnaires in most situations of routine use. These results can reasonably be extended to other questionnaires constructed according to classical test theory.
Bias in phylogenetic reconstruction of vertebrate rhodopsin sequences.
Chang, B S; Campbell, D L
2000-08-01
Two spurious nodes were found in phylogenetic analyses of vertebrate rhodopsin sequences in comparison with well-established vertebrate relationships. These spurious reconstructions were well supported in bootstrap analyses and occurred independently of the method of phylogenetic analysis used (parsimony, distance, or likelihood). Use of this data set of vertebrate rhodopsin sequences allowed us to exploit established vertebrate relationships, as well as the considerable amount known about the molecular evolution of this gene, in order to identify important factors contributing to the spurious reconstructions. Simulation studies using parametric bootstrapping indicate that it is unlikely that the spurious nodes in the parsimony analyses are due to long branches or other topological effects. Rather, they appear to be due to base compositional bias at third positions, codon bias, and convergent evolution at nucleotide positions encoding the hydrophobic residues isoleucine, leucine, and valine. LogDet distance methods, as well as maximum-likelihood methods which allow for nonstationary changes in base composition, reduce but do not entirely eliminate support for the spurious resolutions. Inclusion of five additional rhodopsin sequences in the phylogenetic analyses largely corrected one of the spurious reconstructions while leaving the other unaffected. The additional sequences not only were more proximal to the corrected node, but were also found to have intermediate levels of base composition and codon bias as compared with neighboring sequences on the tree. This study shows that the spurious reconstructions can be corrected either by excluding third positions, as well as those encoding the amino acids Ile, Val, and Leu (which may not be ideal, as these sites can contain useful phylogenetic signal for other parts of the tree), or by the addition of sequences that reduce problems associated with convergent evolution.
Keller, Alexander; Förster, Frank; Müller, Tobias; Dandekar, Thomas; Schultz, Jörg; Wolf, Matthias
2010-01-15
In several studies, secondary structures of ribosomal genes have been used to improve the quality of phylogenetic reconstructions. An extensive evaluation of the benefits of secondary structure, however, is lacking. This is the first study to counter this deficiency. We inspected the accuracy and robustness of phylogenetics with individual secondary structures by simulation experiments for artificial tree topologies with up to 18 taxa and for divergency levels in the range of typical phylogenetic studies. We chose the internal transcribed spacer 2 of the ribosomal cistron as an exemplary marker region. Simulation integrated the coevolution process of sequences with secondary structures. Additionally, the phylogenetic power of marker size duplication was investigated and compared with sequence and sequence-structure reconstruction methods. The results clearly show that accuracy and robustness of Neighbor Joining trees are largely improved by structural information in contrast to sequence only data, whereas a doubled marker size only accounts for robustness. Individual secondary structures of ribosomal RNA sequences provide a valuable gain of information content that is useful for phylogenetics. Thus, the usage of ITS2 sequence together with secondary structure for taxonomic inferences is recommended. Other reconstruction methods as maximum likelihood, bayesian inference or maximum parsimony may equally profit from secondary structure inclusion. This article was reviewed by Shamil Sunyaev, Andrea Tanzer (nominated by Frank Eisenhaber) and Eugene V. Koonin. Reviewed by Shamil Sunyaev, Andrea Tanzer (nominated by Frank Eisenhaber) and Eugene V. Koonin. For the full reviews, please go to the Reviewers' comments section.
The performance of phylogenetic algorithms in estimating haplotype genealogies with migration.
Salzburger, Walter; Ewing, Greg B; Von Haeseler, Arndt
2011-05-01
Genealogies estimated from haplotypic genetic data play a prominent role in various biological disciplines in general and in phylogenetics, population genetics and phylogeography in particular. Several software packages have specifically been developed for the purpose of reconstructing genealogies from closely related, and hence, highly similar haplotype sequence data. Here, we use simulated data sets to test the performance of traditional phylogenetic algorithms, neighbour-joining, maximum parsimony and maximum likelihood in estimating genealogies from nonrecombining haplotypic genetic data. We demonstrate that these methods are suitable for constructing genealogies from sets of closely related DNA sequences with or without migration. As genealogies based on phylogenetic reconstructions are fully resolved, but not necessarily bifurcating, and without reticulations, these approaches outperform widespread 'network' constructing methods. In our simulations of coalescent scenarios involving panmictic, symmetric and asymmetric migration, we found that phylogenetic reconstruction methods performed well, while the statistical parsimony approach as implemented in TCS performed poorly. Overall, parsimony as implemented in the PHYLIP package performed slightly better than other methods. We further point out that we are not making the case that widespread 'network' constructing methods are bad, but that traditional phylogenetic tree finding methods are applicable to haplotypic data and exhibit reasonable performance with respect to accuracy and robustness. We also discuss some of the problems of converting a tree to a haplotype genealogy, in particular that it is nonunique. © 2011 Blackwell Publishing Ltd.
SNPhylo: a pipeline to construct a phylogenetic tree from huge SNP data.
Lee, Tae-Ho; Guo, Hui; Wang, Xiyin; Kim, Changsoo; Paterson, Andrew H
2014-02-26
Phylogenetic trees are widely used for genetic and evolutionary studies in various organisms. Advanced sequencing technology has dramatically enriched data available for constructing phylogenetic trees based on single nucleotide polymorphisms (SNPs). However, massive SNP data makes it difficult to perform reliable analysis, and there has been no ready-to-use pipeline to generate phylogenetic trees from these data. We developed a new pipeline, SNPhylo, to construct phylogenetic trees based on large SNP datasets. The pipeline may enable users to construct a phylogenetic tree from three representative SNP data file formats. In addition, in order to increase reliability of a tree, the pipeline has steps such as removing low quality data and considering linkage disequilibrium. A maximum likelihood method for the inference of phylogeny is also adopted in generation of a tree in our pipeline. Using SNPhylo, users can easily produce a reliable phylogenetic tree from a large SNP data file. Thus, this pipeline can help a researcher focus more on interpretation of the results of analysis of voluminous data sets, rather than manipulations necessary to accomplish the analysis.
Ari, Eszter; Ittzés, Péter; Podani, János; Thi, Quynh Chi Le; Jakó, Eena
2012-04-01
Boolean analysis (or BOOL-AN; Jakó et al., 2009. BOOL-AN: A method for comparative sequence analysis and phylogenetic reconstruction. Mol. Phylogenet. Evol. 52, 887-97.), a recently developed method for sequence comparison uses the Iterative Canonical Form of Boolean functions. It considers sequence information in a way entirely different from standard phylogenetic methods (i.e. Maximum Parsimony, Maximum-Likelihood, Neighbor-Joining, and Bayesian analysis). The performance and reliability of Boolean analysis were tested and compared with the standard phylogenetic methods, using artificially evolved - simulated - nucleotide sequences and the 22 mitochondrial tRNA genes of the great apes. At the outset, we assumed that the phylogeny of Hominidae is generally well established, and the guide tree of artificial sequence evolution can also be used as a benchmark. These offer a possibility to compare and test the performance of different phylogenetic methods. Trees were reconstructed by each method from 2500 simulated sequences and 22 mitochondrial tRNA sequences. We also introduced a special re-sampling method for Boolean analysis on permuted sequence sites, the P-BOOL-AN procedure. Considering the reliability values (branch support values of consensus trees and Robinson-Foulds distances) we used for simulated sequence trees produced by different phylogenetic methods, BOOL-AN appeared as the most reliable method. Although the mitochondrial tRNA sequences of great apes are relatively short (59-75 bases long) and the ratio of their constant characters is about 75%, BOOL-AN, P-BOOL-AN and the Bayesian approach produced the same tree-topology as the established phylogeny, while the outcomes of Maximum Parsimony, Maximum-Likelihood and Neighbor-Joining methods were equivocal. We conclude that Boolean analysis is a promising alternative to existing methods of sequence comparison for phylogenetic reconstruction and congruence analysis. Copyright Â© 2012 Elsevier Inc. All
Likelihood inference for unions of interacting discs
DEFF Research Database (Denmark)
Møller, Jesper; Helisova, K.
2010-01-01
This is probably the first paper which discusses likelihood inference for a random set using a germ-grain model, where the individual grains are unobservable, edge effects occur and other complications appear. We consider the case where the grains form a disc process modelled by a marked point...... process, where the germs are the centres and the marks are the associated radii of the discs. We propose to use a recent parametric class of interacting disc process models, where the minimal sufficient statistic depends on various geometric properties of the random set, and the density is specified......-based maximum likelihood inference and the effect of specifying different reference Poisson models....
Multiple sequence alignment accuracy and phylogenetic inference.
Ogden, T Heath; Rosenberg, Michael S
2006-04-01
Phylogenies are often thought to be more dependent upon the specifics of the sequence alignment rather than on the method of reconstruction. Simulation of sequences containing insertion and deletion events was performed in order to determine the role that alignment accuracy plays during phylogenetic inference. Data sets were simulated for pectinate, balanced, and random tree shapes under different conditions (ultrametric equal branch length, ultrametric random branch length, nonultrametric random branch length). Comparisons between hypothesized alignments and true alignments enabled determination of two measures of alignment accuracy, that of the total data set and that of individual branches. In general, our results indicate that as alignment error increases, topological accuracy decreases. This trend was much more pronounced for data sets derived from more pectinate topologies. In contrast, for balanced, ultrametric, equal branch length tree shapes, alignment inaccuracy had little average effect on tree reconstruction. These conclusions are based on average trends of many analyses under different conditions, and any one specific analysis, independent of the alignment accuracy, may recover very accurate or inaccurate topologies. Maximum likelihood and Bayesian, in general, outperformed neighbor joining and maximum parsimony in terms of tree reconstruction accuracy. Results also indicated that as the length of the branch and of the neighboring branches increase, alignment accuracy decreases, and the length of the neighboring branches is the major factor in topological accuracy. Thus, multiple-sequence alignment can be an important factor in downstream effects on topological reconstruction.
Earthquake likelihood model testing
Schorlemmer, D.; Gerstenberger, M.C.; Wiemer, S.; Jackson, D.D.; Rhoades, D.A.
2007-01-01
INTRODUCTIONThe Regional Earthquake Likelihood Models (RELM) project aims to produce and evaluate alternate models of earthquake potential (probability per unit volume, magnitude, and time) for California. Based on differing assumptions, these models are produced to test the validity of their assumptions and to explore which models should be incorporated in seismic hazard and risk evaluation. Tests based on physical and geological criteria are useful but we focus on statistical methods using future earthquake catalog data only. We envision two evaluations: a test of consistency with observed data and a comparison of all pairs of models for relative consistency. Both tests are based on the likelihood method, and both are fully prospective (i.e., the models are not adjusted to fit the test data). To be tested, each model must assign a probability to any possible event within a specified region of space, time, and magnitude. For our tests the models must use a common format: earthquake rates in specified “bins” with location, magnitude, time, and focal mechanism limits.Seismology cannot yet deterministically predict individual earthquakes; however, it should seek the best possible models for forecasting earthquake occurrence. This paper describes the statistical rules of an experiment to examine and test earthquake forecasts. The primary purposes of the tests described below are to evaluate physical models for earthquakes, assure that source models used in seismic hazard and risk studies are consistent with earthquake data, and provide quantitative measures by which models can be assigned weights in a consensus model or be judged as suitable for particular regions.In this paper we develop a statistical method for testing earthquake likelihood models. A companion paper (Schorlemmer and Gerstenberger 2007, this issue) discusses the actual implementation of these tests in the framework of the RELM initiative.Statistical testing of hypotheses is a common task and a
Directory of Open Access Journals (Sweden)
Vidal-Russell Romina
2004-10-01
Full Text Available Abstract Background The phylogenetic relationships among the holoparasites of Rafflesiales have remained enigmatic for over a century. Recent molecular phylogenetic studies using the mitochondrial matR gene placed Rafflesia, Rhizanthes and Sapria (Rafflesiaceae s. str. in the angiosperm order Malpighiales and Mitrastema (Mitrastemonaceae in Ericales. These phylogenetic studies did not, however, sample two additional groups traditionally classified within Rafflesiales (Apodantheaceae and Cytinaceae. Here we provide molecular phylogenetic evidence using DNA sequence data from mitochondrial and nuclear genes for representatives of all genera in Rafflesiales. Results Our analyses indicate that the phylogenetic affinities of the large-flowered clade and Mitrastema, ascertained using mitochondrial matR, are congruent with results from nuclear SSU rDNA when these data are analyzed using maximum likelihood and Bayesian methods. The relationship of Cytinaceae to Malvales was recovered in all analyses. Relationships between Apodanthaceae and photosynthetic angiosperms varied depending upon the data partition: Malvales (3-gene, Cucurbitales (matR or Fabales (atp1. The latter incongruencies suggest that horizontal gene transfer (HGT may be affecting the mitochondrial gene topologies. The lack of association between Mitrastema and Ericales using atp1 is suggestive of HGT, but greater sampling within eudicots is needed to test this hypothesis further. Conclusions Rafflesiales are not monophyletic but composed of three or four independent lineages (families: Rafflesiaceae, Mitrastemonaceae, Apodanthaceae and Cytinaceae. Long-branch attraction appears to be misleading parsimony analyses of nuclear small-subunit rDNA data, but model-based methods (maximum likelihood and Bayesian analyses recover a topology that is congruent with the mitochondrial matR gene tree, thus providing compelling evidence for organismal relationships. Horizontal gene transfer appears to
Likelihood inference for unions of interacting discs
DEFF Research Database (Denmark)
Møller, Jesper; Helisová, Katarina
To the best of our knowledge, this is the first paper which discusses likelihood inference or a random set using a germ-grain model, where the individual grains are unobservable edge effects occur, and other complications appear. We consider the case where the grains form a disc process modelled...... is specified with respect to a given marked Poisson model (i.e. a Boolean model). We show how edge effects and other complications can be handled by considering a certain conditional likelihood. Our methodology is illustrated by analyzing Peter Diggle's heather dataset, where we discuss the results...... of simulation-based maximum likelihood inference and the effect of specifying different reference Poisson models....
Ayres, Daniel L; Darling, Aaron; Zwickl, Derrick J; Beerli, Peter; Holder, Mark T; Lewis, Paul O; Huelsenbeck, John P; Ronquist, Fredrik; Swofford, David L; Cummings, Michael P; Rambaut, Andrew; Suchard, Marc A
2012-01-01
Phylogenetic inference is fundamental to our understanding of most aspects of the origin and evolution of life, and in recent years, there has been a concentration of interest in statistical approaches such as Bayesian inference and maximum likelihood estimation. Yet, for large data sets and realistic or interesting models of evolution, these approaches remain computationally demanding. High-throughput sequencing can yield data for thousands of taxa, but scaling to such problems using serial computing often necessitates the use of nonstatistical or approximate approaches. The recent emergence of graphics processing units (GPUs) provides an opportunity to leverage their excellent floating-point computational performance to accelerate statistical phylogenetic inference. A specialized library for phylogenetic calculation would allow existing software packages to make more effective use of available computer hardware, including GPUs. Adoption of a common library would also make it easier for other emerging computing architectures, such as field programmable gate arrays, to be used in the future. We present BEAGLE, an application programming interface (API) and library for high-performance statistical phylogenetic inference. The API provides a uniform interface for performing phylogenetic likelihood calculations on a variety of compute hardware platforms. The library includes a set of efficient implementations and can currently exploit hardware including GPUs using NVIDIA CUDA, central processing units (CPUs) with Streaming SIMD Extensions and related processor supplementary instruction sets, and multicore CPUs via OpenMP. To demonstrate the advantages of a common API, we have incorporated the library into several popular phylogenetic software packages. The BEAGLE library is free open source software licensed under the Lesser GPL and available from http://beagle-lib.googlecode.com. An example client program is available as public domain software.
Detection and phylogenetic analysis of bacteriophage WO in spiders (Araneae).
Yan, Qian; Qiao, Huping; Gao, Jin; Yun, Yueli; Liu, Fengxiang; Peng, Yu
2015-11-01
Phage WO is a bacteriophage found in Wolbachia. Herein, we represent the first phylogenetic study of WOs that infect spiders (Araneae). Seven species of spiders (Araneus alternidens, Nephila clavata, Hylyphantes graminicola, Prosoponoides sinensis, Pholcus crypticolens, Coleosoma octomaculatum, and Nurscia albofasciata) from six families were infected by Wolbachia and WO, followed by comprehensive sequence analysis. Interestingly, WO could be only detected Wolbachia-infected spiders. The relative infection rates of those seven species of spiders were 75, 100, 88.9, 100, 62.5, 72.7, and 100 %, respectively. Our results indicated that both Wolbachia and WO were found in three different body parts of N. clavata, and WO could be passed to the next generation of H. graminicola by vertical transmission. There were three different sequences for WO infected in A. alternidens and two different WO sequences from C. octomaculatum. Only one sequence of WO was found for the other five species of spiders. The discovered sequence of WO ranged from 239 to 311 bp. Phylogenetic tree was generated using maximum likelihood (ML) based on the orf7 gene sequences. According to the phylogenetic tree, WOs in N. clavata and H. graminicola were clustered in the same group. WOs from A. alternidens (WAlt1) and C. octomaculatum (WOct2) were closely related to another clade, whereas WO in P. sinensis was classified as a sole cluster.
Eder, Wolfgang; Ives Torres-Silva, Ana; Hohenegger, Johann
2017-04-01
Phylogenetic analysis and trees based on molecular data are broadly applied and used to infer genetical and biogeographic relationship in recent larger foraminifera. Molecular phylogenetic is intensively used within recent nummulitids, however for fossil representatives these trees are only of minor informational value. Hence, within paleontological studies a phylogenetic approach through morphometric analysis is of much higher value. To tackle phylogenetic relationships within the nummulitid family, a much higher number of morphological character must be measured than are commonly used in biometric studies, where mostly parameters describing embryonic size (e.g., proloculus diameter, deuteroloculus diameter) and/or the marginal spiral (e.g., spiral diagrams, spiral indices) are studied. For this purpose 11 growth-independent and/or growth-invariant characters have been used to describe the morphological variability of equatorial thin sections of seven Carribbean nummulitid taxa (Nummulites striatoreticulatus, N. macgillavry, Palaeonummulites willcoxi, P.floridensis, P. soldadensis, P.trinitatensis and P.ocalanus) and one outgroup taxon (Ranikothalia bermudezi). Using these characters, phylogenetic trees were calculated using a restricted maximum likelihood algorithm (REML), and results are cross-checked by ordination and cluster analysis. Square-change parsimony method has been run to reconstruct ancestral states, as well as to simulate the evolution of the chosen characters along the calculated phylogenetic tree and, independent - contrast analysis was used to estimate confidence intervals. Based on these simulations, phylogenetic tendencies of certain characters proposed for nummulitids (e.g., Cope's rule or nepionic acceleration) can be tested, whether these tendencies are valid for the whole family or only for certain clades. At least, within the Carribean nummulitids, phylogenetic trends along some growth-independent characters of the embryo (e.g., first
Dor, Roi; Carling, Matthew D; Lovette, Irby J; Sheldon, Frederick H; Winkler, David W
2012-10-01
The New World swallow genus Tachycineta comprises nine species that collectively have a wide geographic distribution and remarkable variation both within- and among-species in ecologically important traits. Existing phylogenetic hypotheses for Tachycineta are based on mitochondrial DNA sequences, thus they provide estimates of a single gene tree. In this study we sequenced multiple individuals from each species at 16 nuclear intron loci. We used gene concatenated approaches (Bayesian and maximum likelihood) as well as coalescent-based species tree inference to reconstruct phylogenetic relationships of the genus. We examined the concordance and conflict between the nuclear and mitochondrial trees and between concatenated and coalescent-based inferences. Our results provide an alternative phylogenetic hypothesis to the existing mitochondrial DNA estimate of phylogeny. This new hypothesis provides a more accurate framework in which to explore trait evolution and examine the evolution of the mitochondrial genome in this group. Copyright © 2012 Elsevier Inc. All rights reserved.
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Anna Claudia Baumel Mongruel
2017-08-01
Full Text Available Abstract Wild animals play an important role in carrying vectors that may potentially transmit pathogens. Several reports highlighted the participation of wild animals on the Anaplasma phagocytophilum cycle, including as hosts of the agent. The aim of this study was to report the molecular detection of an agent phylogenetically related to A. phagocytophilum isolated from a wild bird in the Midwest of the state of Paraná, Brazil. Fifteen blood samples were collected from eleven different bird species in the Guarapuava region. One sample collected from a Penelope obscura bird was positive in nested PCR targeting the 16S rRNA gene of Anaplasma spp. The phylogenetic tree based on the Maximum Likelihood analysis showed that the sequence obtained was placed in the same clade with A. phagocytophilum isolated from domestic cats in Brazil. The present study reports the first molecular detection of a phylogenetically related A. phagocytophilum bacterium in a bird from Paraná State.
A RAD-based phylogenetics for Orestias fishes from Lake Titicaca.
Takahashi, Tetsumi; Moreno, Edmundo
2015-12-01
The fish genus Orestias is endemic to the Andes highlands, and Lake Titicaca is the centre of the species diversity of the genus. Previous phylogenetic studies based on a single locus of mitochondrial and nuclear DNA strongly support the monophyly of a group composed of many of species endemic to the Lake Titicaca basin (the Lake Titicaca radiation), but the relationships among the species in the radiation remain unclear. Recently, restriction site-associated DNA (RAD) sequencing, which can produce a vast number of short sequences from various loci of nuclear DNA, has emerged as a useful way to resolve complex phylogenetic problems. To propose a new phylogenetic hypothesis of Orestias fishes of the Lake Titicaca radiation, we conducted a cluster analysis based on morphological similarities among fish samples and a molecular phylogenetic analysis based on RAD sequencing. From a morphological cluster analysis, we recognised four species groups in the radiation, and three of the four groups were resolved as monophyletic groups in maximum-likelihood trees based on RAD sequencing data. The other morphology-based group was not resolved as a monophyletic group in molecular phylogenies, and some members of the group were diverged from its sister group close to the root of the Lake Titicaca radiation. The evolution of these fishes is discussed from the phylogenetic relationships. Copyright © 2015 Elsevier Inc. All rights reserved.
Baldo, A M; Les, D H; Strausbaugh, L D
1999-11-01
Simplified DNA sequence acquisition has provided many new data sets that are useful for phylogenetic reconstruction, including single- and multiple-copy nuclear and organellar genes. Although transcribed regions receive much attention, nontranscribed regions have recently been added to the repertoire of sequences suitable for phylogenetic studies, especially for closely related taxa. We evaluated the efficacy of a small portion of the histone repeat for phylogenetic reconstruction among Drosophila species. Histone repeats in invertebrates offer distinct advantages similar to those of widely used ribosomal repeats. First, the units are tandemly repeated and undergo concerted evolution. Second, histone repeats include both highly conserved coding and variable intergenic regions. This composition facilitates application of "universal" primers spanning potentially informative sites. We examined a small region of the histone repeat, including the intergenic spacer segments of coding regions from the divergently transcribed H2A and H2B histone genes. The spacer (about 230 bp) exists as a mosaic with highly conserved functional motifs interspersed with rapidly diverging regions; the former aid in alignment of the spacer. There are no ambiguities in alignment of coding regions. Coding and noncoding regions were analyzed together and separately for phylogenetic information. Parsimony, distance, and maximum-likelihood methods successfully retrieve the corroborated phylogeny for the taxa examined. This study demonstrates the resolving power of a small histone region which may now be added to the growing collection of phylogenetically useful DNA sequences.
First phylogenetic analysis of Ehrlichia canis in dogs and ticks from Mexico. Preliminary study
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Carolina G. Sosa-Gutiérrez
2016-09-01
Full Text Available Objective. Phylogenetic characterization of Ehrlichia canis in dogs naturally infected and ticks, diagnosed by PCR and sequencing of 16SrRNA gene; compare different isolates found in American countries. Materials and methods. Were collected Blood samples from 139 dogs with suggestive clinical manifestations of this disease and they were infested with ticks; part of 16SrRNA gene was sequenced and aligned, with 17 sequences reported in American countries. Two phylogenetic trees were constructed using the Maximum likelihood method, and Maximum parsimony. Results. They were positive to E. canis 25/139 (18.0% dogs and 29/139 (20.9% ticks. The clinical manifestations presented were fever, fatigue, depression and vomiting. Rhipicephalus sanguineus Dermacentor variabilis and Haemaphysalis leporis-palustris ticks were positive for E. canis. Phylogenetic analysis showed that the sequences of dogs and ticks in Mexico form a third group diverging of sequences from South America and USA. Conclusions. This is the first phylogenetic analysis of E. canis in Mexico. There are differences in the sequences of Mexico with those reported in South America and USA. This research lays the foundation for further study of genetic variability.
Applying a multiobjective metaheuristic inspired by honey bees to phylogenetic inference.
Santander-Jiménez, Sergio; Vega-Rodríguez, Miguel A
2013-10-01
The development of increasingly popular multiobjective metaheuristics has allowed bioinformaticians to deal with optimization problems in computational biology where multiple objective functions must be taken into account. One of the most relevant research topics that can benefit from these techniques is phylogenetic inference. Throughout the years, different researchers have proposed their own view about the reconstruction of ancestral evolutionary relationships among species. As a result, biologists often report different phylogenetic trees from a same dataset when considering distinct optimality principles. In this work, we detail a multiobjective swarm intelligence approach based on the novel Artificial Bee Colony algorithm for inferring phylogenies. The aim of this paper is to propose a complementary view of phylogenetics according to the maximum parsimony and maximum likelihood criteria, in order to generate a set of phylogenetic trees that represent a compromise between these principles. Experimental results on a variety of nucleotide data sets and statistical studies highlight the relevance of the proposal with regard to other multiobjective algorithms and state-of-the-art biological methods. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.
A phylogenetic reconstruction and emendation of Agaricus section Duploannulatae.
Challen, Michael P; Kerrigan, Richard W; Callac, Philippe
2003-01-01
Agaricus section Duploannulatae comprises the group of species allied with A. bisporus and A. bitorquis. Disagreement exists in the literature regarding the composition of this group. We used DNA sequence data from the ITS segments of the nuclear ribosomal DNA region, in a sample of European and North American isolates, to identify characters shared by this group, to further delimit species-level taxa within the section, and to develop a phylogenetic hypothesis. Shared polymorphisms that suggest a natural limit for section Duploannulatae were found. ITS1 data were assessed using parsimony, distance and maximum likelihood methods of phylogeny. The section Duploannulatae comprised six robust clades. Five clades corresponded to well characterized species from the temperate Northern Hemisphere (A. bisporus, A. subfloccosus, A. bitorquis, A. vaporarius, A. cupressicola). The sixth clade encompassed an A. devoniensis complex. Species concepts, nomenclature, and relationships are discussed and compared with prior reports.
Martínez-Aquino, Andrés; Vidal-Martínez, Victor M; Aguirre-Macedo, M Leopoldina
2017-01-01
The phylogenetic position of three taxa from two trematode genera, belonging to the subfamily Acanthostominae (Opisthorchioidea: Cryptogonimidae), were analysed using partial 28S ribosomal DNA (Domains 1-2) and internal transcribed spacers (ITS1-5.8S-ITS2). Bayesian inference and Maximum likelihood analyses of combined 28S rDNA and ITS1 + 5.8S + ITS2 sequences indicated the monophyly of the genus Acanthostomum ( A. cf. americanum and A. burminis ) and paraphyly of the Acanthostominae . These phylogenetic relationships were consistent in analyses of 28S alone and concatenated 28S + ITS1 + 5.8S + ITS2 sequences analyses. Based on molecular phylogenetic analyses, the subfamily Acanthostominae is therefore a paraphyletic taxon, in contrast with previous classifications based on morphological data. Phylogenetic patterns of host specificity inferred from adult stages of other cryptogonimid taxa are also well supported. However, analyses using additional genera and species are necessary to support the phylogenetic inferences from this study. Our molecular phylogenetic reconstruction linked two larval stages of A. cf. americanum cercariae and metacercariae. Here, we present the evolutionary and ecological implications of parasitic infections in freshwater and brackish environments.
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Andrés Martínez-Aquino
2017-12-01
Full Text Available The phylogenetic position of three taxa from two trematode genera, belonging to the subfamily Acanthostominae (Opisthorchioidea: Cryptogonimidae, were analysed using partial 28S ribosomal DNA (Domains 1–2 and internal transcribed spacers (ITS1–5.8S–ITS2. Bayesian inference and Maximum likelihood analyses of combined 28S rDNA and ITS1 + 5.8S + ITS2 sequences indicated the monophyly of the genus Acanthostomum (A. cf. americanum and A. burminis and paraphyly of the Acanthostominae. These phylogenetic relationships were consistent in analyses of 28S alone and concatenated 28S + ITS1 + 5.8S + ITS2 sequences analyses. Based on molecular phylogenetic analyses, the subfamily Acanthostominae is therefore a paraphyletic taxon, in contrast with previous classifications based on morphological data. Phylogenetic patterns of host specificity inferred from adult stages of other cryptogonimid taxa are also well supported. However, analyses using additional genera and species are necessary to support the phylogenetic inferences from this study. Our molecular phylogenetic reconstruction linked two larval stages of A. cf. americanum cercariae and metacercariae. Here, we present the evolutionary and ecological implications of parasitic infections in freshwater and brackish environments.
Abu Salim, Kamariah; Chase, Mark W.; Dexter, Kyle G.; Pennington, R. Toby; Tan, Sylvester; Kaye, Maria Ellen; Samuel, Rosabelle
2017-01-01
DNA barcoding is a fast and reliable tool to assess and monitor biodiversity and, via community phylogenetics, to investigate ecological and evolutionary processes that may be responsible for the community structure of forests. In this study, DNA barcodes for the two widely used plastid coding regions rbcL and matK are used to contribute to identification of morphologically undetermined individuals, as well as to investigate phylogenetic structure of tree communities in 70 subplots (10 × 10m) of a 25-ha forest-dynamics plot in Brunei (Borneo, Southeast Asia). The combined matrix (rbcL + matK) comprised 555 haplotypes (from ≥154 genera, 68 families and 25 orders sensu APG, Angiosperm Phylogeny Group, 2016), making a substantial contribution to tree barcode sequences from Southeast Asia. Barcode sequences were used to reconstruct phylogenetic relationships using maximum likelihood, both with and without constraining the topology of taxonomic orders to match that proposed by the Angiosperm Phylogeny Group. A third phylogenetic tree was reconstructed using the program Phylomatic to investigate the influence of phylogenetic resolution on results. Detection of non-random patterns of community assembly was determined by net relatedness index (NRI) and nearest taxon index (NTI). In most cases, community assembly was either random or phylogenetically clustered, which likely indicates the importance to community structure of habitat filtering based on phylogenetically correlated traits in determining community structure. Different phylogenetic trees gave similar overall results, but the Phylomatic tree produced greater variation across plots for NRI and NTI values, presumably due to noise introduced by using an unresolved phylogenetic tree. Our results suggest that using a DNA barcode tree has benefits over the traditionally used Phylomatic approach by increasing precision and accuracy and allowing the incorporation of taxonomically unidentified individuals into analyses
Directory of Open Access Journals (Sweden)
Jacqueline Heckenhauer
Full Text Available DNA barcoding is a fast and reliable tool to assess and monitor biodiversity and, via community phylogenetics, to investigate ecological and evolutionary processes that may be responsible for the community structure of forests. In this study, DNA barcodes for the two widely used plastid coding regions rbcL and matK are used to contribute to identification of morphologically undetermined individuals, as well as to investigate phylogenetic structure of tree communities in 70 subplots (10 × 10m of a 25-ha forest-dynamics plot in Brunei (Borneo, Southeast Asia. The combined matrix (rbcL + matK comprised 555 haplotypes (from ≥154 genera, 68 families and 25 orders sensu APG, Angiosperm Phylogeny Group, 2016, making a substantial contribution to tree barcode sequences from Southeast Asia. Barcode sequences were used to reconstruct phylogenetic relationships using maximum likelihood, both with and without constraining the topology of taxonomic orders to match that proposed by the Angiosperm Phylogeny Group. A third phylogenetic tree was reconstructed using the program Phylomatic to investigate the influence of phylogenetic resolution on results. Detection of non-random patterns of community assembly was determined by net relatedness index (NRI and nearest taxon index (NTI. In most cases, community assembly was either random or phylogenetically clustered, which likely indicates the importance to community structure of habitat filtering based on phylogenetically correlated traits in determining community structure. Different phylogenetic trees gave similar overall results, but the Phylomatic tree produced greater variation across plots for NRI and NTI values, presumably due to noise introduced by using an unresolved phylogenetic tree. Our results suggest that using a DNA barcode tree has benefits over the traditionally used Phylomatic approach by increasing precision and accuracy and allowing the incorporation of taxonomically unidentified individuals
Klopfstein, Seraina; Kropf, Christian; Quicke, Donald L J
2010-03-01
How to quantify the phylogenetic information content of a data set is a longstanding question in phylogenetics, influencing both the assessment of data quality in completed studies and the planning of future phylogenetic projects. Recently, a method has been developed that profiles the phylogenetic informativeness (PI) of a data set through time by linking its site-specific rates of change to its power to resolve relationships at different timescales. Here, we evaluate the performance of this method in the case of 2 standard genetic markers for phylogenetic reconstruction, 28S ribosomal RNA and cytochrome oxidase subunit 1 (CO1) mitochondrial DNA, with maximum parsimony, maximum likelihood, and Bayesian analyses of relationships within a group of parasitoid wasps (Hymenoptera: Ichneumonidae, Diplazontinae). Retrieving PI profiles of the 2 genes from our own and from 3 additional data sets, we find that the method repeatedly overestimates the performance of the more quickly evolving CO1 compared with 28S. We explore possible reasons for this bias, including phylogenetic uncertainty, violation of the molecular clock assumption, model misspecification, and nonstationary nucleotide composition. As none of these provides a sufficient explanation of the observed discrepancy, we use simulated data sets, based on an idealized setting, to show that the optimum evolutionary rate decreases with increasing number of taxa. We suggest that this relationship could explain why the formula derived from the 4-taxon case overrates the performance of higher versus lower rates of evolution in our case and that caution should be taken when the method is applied to data sets including more than 4 taxa.
PAL: an object-oriented programming library for molecular evolution and phylogenetics.
Drummond, A; Strimmer, K
2001-07-01
Phylogenetic Analysis Library (PAL) is a collection of Java classes for use in molecular evolution and phylogenetics. PAL provides a modular environment for the rapid construction of both special-purpose and general analysis programs. PAL version 1.1 consists of 145 public classes or interfaces in 13 packages, including classes for models of character evolution, maximum-likelihood estimation, and the coalescent, with a total of more than 27000 lines of code. The PAL project is set up as a collaborative project to facilitate contributions from other researchers. AVAILIABILTY: The program is free and is available at http://www.pal-project.org. It requires Java 1.1 or later. PAL is licensed under the GNU General Public License.
Assessment of phylogenetic sensitivity for reconstructing HIV-1 epidemiological relationships.
Beloukas, Apostolos; Magiorkinis, Emmanouil; Magiorkinis, Gkikas; Zavitsanou, Asimina; Karamitros, Timokratis; Hatzakis, Angelos; Paraskevis, Dimitrios
2012-06-01
Phylogenetic analysis has been extensively used as a tool for the reconstruction of epidemiological relations for research or for forensic purposes. It was our objective to assess the sensitivity of different phylogenetic methods and various phylogenetic programs to reconstruct epidemiological links among HIV-1 infected patients that is the probability to reveal a true transmission relationship. Multiple datasets (90) were prepared consisting of HIV-1 sequences in protease (PR) and partial reverse transcriptase (RT) sampled from patients with documented epidemiological relationship (target population), and from unrelated individuals (control population) belonging to the same HIV-1 subtype as the target population. Each dataset varied regarding the number, the geographic origin and the transmission risk groups of the sequences among the control population. Phylogenetic trees were inferred by neighbor-joining (NJ), maximum likelihood heuristics (hML) and Bayesian methods. All clusters of sequences belonging to the target population were correctly reconstructed by NJ and Bayesian methods receiving high bootstrap and posterior probability (PP) support, respectively. On the other hand, TreePuzzle failed to reconstruct or provide significant support for several clusters; high puzzling step support was associated with the inclusion of control sequences from the same geographic area as the target population. In contrary, all clusters were correctly reconstructed by hML as implemented in PhyML 3.0 receiving high bootstrap support. We report that under the conditions of our study, hML using PhyML, NJ and Bayesian methods were the most sensitive for the reconstruction of epidemiological links mostly from sexually infected individuals. Copyright © 2012 Elsevier B.V. All rights reserved.
Analysis of Acorus calamus chloroplast genome and its phylogenetic implications.
Goremykin, Vadim V; Holland, Barbara; Hirsch-Ernst, Karen I; Hellwig, Frank H
2005-09-01
Determining the phylogenetic relationships among the major lines of angiosperms is a long-standing problem, yet the uncertainty as to the phylogenetic affinity of these lines persists. While a number of studies have suggested that the ANITA (Amborella-Nymphaeales-Illiciales-Trimeniales-Aristolochiales) grade is basal within angiosperms, studies of complete chloroplast genome sequences also suggested an alternative tree, wherein the line leading to the grasses branches first among the angiosperms. To improve taxon sampling in the existing chloroplast genome data, we sequenced the chloroplast genome of the monocot Acorus calamus. We generated a concatenated alignment (89,436 positions for 15 taxa), encompassing almost all sequences usable for phylogeny reconstruction within spermatophytes. The data still contain support for both the ANITA-basal and grasses-basal hypotheses. Using simulations we can show that were the ANITA-basal hypothesis true, parsimony (and distance-based methods with many models) would be expected to fail to recover it. The self-evident explanation for this failure appears to be a long-branch attraction (LBA) between the clade of grasses and the out-group. However, this LBA cannot explain the discrepancies observed between tree topology recovered using the maximum likelihood (ML) method and the topologies recovered using the parsimony and distance-based methods when grasses are deleted. Furthermore, the fact that neither maximum parsimony nor distance methods consistently recover the ML tree, when according to the simulations they would be expected to, when the out-group (Pinus) is deleted, suggests that either the generating tree is not correct or the best symmetric model is misspecified (or both). We demonstrate that the tree recovered under ML is extremely sensitive to model specification and that the best symmetric model is misspecified. Hence, we remain agnostic regarding phylogenetic relationships among basal angiosperm lineages.
Al-Atiyat, R M; Aljumaah, R S
2014-08-27
This study aimed to estimate evolutionary distances and to reconstruct phylogeny trees between different Awassi sheep populations. Thirty-two sheep individuals from three different geographical areas of Jordan and the Kingdom of Saudi Arabia (KSA) were randomly sampled. DNA was extracted from the tissue samples and sequenced using the T7 promoter universal primer. Different phylogenetic trees were reconstructed from 0.64-kb DNA sequences using the MEGA software with the best general time reverse distance model. Three methods of distance estimation were then used. The maximum composite likelihood test was considered for reconstructing maximum likelihood, neighbor-joining and UPGMA trees. The maximum likelihood tree indicated three major clusters separated by cytosine (C) and thymine (T). The greatest distance was shown between the South sheep and North sheep. On the other hand, the KSA sheep as an outgroup showed shorter evolutionary distance to the North sheep population than to the others. The neighbor-joining and UPGMA trees showed quite reliable clusters of evolutionary differentiation of Jordan sheep populations from the Saudi population. The overall results support geographical information and ecological types of the sheep populations studied. Summing up, the resulting phylogeny trees may contribute to the limited information about the genetic relatedness and phylogeny of Awassi sheep in nearby Arab countries.
Using ESTs for phylogenomics: Can one accurately infer a phylogenetic tree from a gappy alignment?
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Hartmann Stefanie
2008-03-01
Full Text Available Abstract Background While full genome sequences are still only available for a handful of taxa, large collections of partial gene sequences are available for many more. The alignment of partial gene sequences results in a multiple sequence alignment containing large gaps that are arranged in a staggered pattern. The consequences of this pattern of missing data on the accuracy of phylogenetic analysis are not well understood. We conducted a simulation study to determine the accuracy of phylogenetic trees obtained from gappy alignments using three commonly used phylogenetic reconstruction methods (Neighbor Joining, Maximum Parsimony, and Maximum Likelihood and studied ways to improve the accuracy of trees obtained from such datasets. Results We found that the pattern of gappiness in multiple sequence alignments derived from partial gene sequences substantially compromised phylogenetic accuracy even in the absence of alignment error. The decline in accuracy was beyond what would be expected based on the amount of missing data. The decline was particularly dramatic for Neighbor Joining and Maximum Parsimony, where the majority of gappy alignments contained 25% to 40% incorrect quartets. To improve the accuracy of the trees obtained from a gappy multiple sequence alignment, we examined two approaches. In the first approach, alignment masking, potentially problematic columns and input sequences are excluded from from the dataset. Even in the absence of alignment error, masking improved phylogenetic accuracy up to 100-fold. However, masking retained, on average, only 83% of the input sequences. In the second approach, alignment subdivision, the missing data is statistically modelled in order to retain as many sequences as possible in the phylogenetic analysis. Subdivision resulted in more modest improvements to alignment accuracy, but succeeded in including almost all of the input sequences. Conclusion These results demonstrate that partial gene
Using ESTs for phylogenomics: can one accurately infer a phylogenetic tree from a gappy alignment?
Hartmann, Stefanie; Vision, Todd J
2008-03-26
While full genome sequences are still only available for a handful of taxa, large collections of partial gene sequences are available for many more. The alignment of partial gene sequences results in a multiple sequence alignment containing large gaps that are arranged in a staggered pattern. The consequences of this pattern of missing data on the accuracy of phylogenetic analysis are not well understood. We conducted a simulation study to determine the accuracy of phylogenetic trees obtained from gappy alignments using three commonly used phylogenetic reconstruction methods (Neighbor Joining, Maximum Parsimony, and Maximum Likelihood) and studied ways to improve the accuracy of trees obtained from such datasets. We found that the pattern of gappiness in multiple sequence alignments derived from partial gene sequences substantially compromised phylogenetic accuracy even in the absence of alignment error. The decline in accuracy was beyond what would be expected based on the amount of missing data. The decline was particularly dramatic for Neighbor Joining and Maximum Parsimony, where the majority of gappy alignments contained 25% to 40% incorrect quartets. To improve the accuracy of the trees obtained from a gappy multiple sequence alignment, we examined two approaches. In the first approach, alignment masking, potentially problematic columns and input sequences are excluded from from the dataset. Even in the absence of alignment error, masking improved phylogenetic accuracy up to 100-fold. However, masking retained, on average, only 83% of the input sequences. In the second approach, alignment subdivision, the missing data is statistically modelled in order to retain as many sequences as possible in the phylogenetic analysis. Subdivision resulted in more modest improvements to alignment accuracy, but succeeded in including almost all of the input sequences. These results demonstrate that partial gene sequences and gappy multiple sequence alignments can pose a
Krajewski, C; Fain, M G; Buckley, L; King, D G
1999-11-01
ki ctes over whether molecular sequence data should be partitioned for phylogenetic analysis often confound two types of heterogeneity among partitions. We distinguish historical heterogeneity (i.e., different partitions have different evolutionary relationships) from dynamic heterogeneity (i.e., different partitions show different patterns of sequence evolution) and explore the impact of the latter on phylogenetic accuracy and precision with a two-gene, mitochondrial data set for cranes. The well-established phylogeny of cranes allows us to contrast tree-based estimates of relevant parameter values with estimates based on pairwise comparisons and to ascertain the effects of incorporating different amounts of process information into phylogenetic estimates. We show that codon positions in the cytochrome b and NADH dehydrogenase subunit 6 genes are dynamically heterogenous under both Poisson and invariable-sites + gamma-rates versions of the F84 model and that heterogeneity includes variation in base composition and transition bias as well as substitution rate. Estimates of transition-bias and relative-rate parameters from pairwise sequence comparisons were comparable to those obtained as tree-based maximum likelihood estimates. Neither rate-category nor mixed-model partitioning strategies resulted in a loss of phylogenetic precision relative to unpartitioned analyses. We suggest that weighted-average distances provide a computationally feasible alternative to direct maximum likelihood estimates of phylogeny for mixed-model analyses of large, dynamically heterogenous data sets. Copyright 1999 Academic Press.
DendroBLAST: approximate phylogenetic trees in the absence of multiple sequence alignments.
Kelly, Steven; Maini, Philip K
2013-01-01
The rapidly growing availability of genome information has created considerable demand for both fast and accurate phylogenetic inference algorithms. We present a novel method called DendroBLAST for reconstructing phylogenetic dendrograms/trees from protein sequences using BLAST. This method differs from other methods by incorporating a simple model of sequence evolution to test the effect of introducing sequence changes on the reliability of the bipartitions in the inferred tree. Using realistic simulated sequence data we demonstrate that this method produces phylogenetic trees that are more accurate than other commonly-used distance based methods though not as accurate as maximum likelihood methods from good quality multiple sequence alignments. In addition to tests on simulated data, we use DendroBLAST to generate input trees for a supertree reconstruction of the phylogeny of the Archaea. This independent analysis produces an approximate phylogeny of the Archaea that has both high precision and recall when compared to previously published analysis of the same dataset using conventional methods. Taken together these results demonstrate that approximate phylogenetic trees can be produced in the absence of multiple sequence alignments, and we propose that these trees will provide a platform for improving and informing downstream bioinformatic analysis. A web implementation of the DendroBLAST method is freely available for use at http://www.dendroblast.com/.
Phylogenetic Information Content of Copepoda Ribosomal DNA Repeat Units: ITS1 and ITS2 Impact
Zagoskin, Maxim V.; Lazareva, Valentina I.; Grishanin, Andrey K.; Mukha, Dmitry V.
2014-01-01
The utility of various regions of the ribosomal repeat unit for phylogenetic analysis was examined in 16 species representing four families, nine genera, and two orders of the subclass Copepoda (Crustacea). Fragments approximately 2000 bp in length containing the ribosomal DNA (rDNA) 18S and 28S gene fragments, the 5.8S gene, and the internal transcribed spacer regions I and II (ITS1 and ITS2) were amplified and analyzed. The DAMBE (Data Analysis in Molecular Biology and Evolution) software was used to analyze the saturation of nucleotide substitutions; this test revealed the suitability of both the 28S gene fragment and the ITS1/ITS2 rDNA regions for the reconstruction of phylogenetic trees. Distance (minimum evolution) and probabilistic (maximum likelihood, Bayesian) analyses of the data revealed that the 28S rDNA and the ITS1 and ITS2 regions are informative markers for inferring phylogenetic relationships among families of copepods and within the Cyclopidae family and associated genera. Split-graph analysis of concatenated ITS1/ITS2 rDNA regions of cyclopoid copepods suggested that the Mesocyclops, Thermocyclops, and Macrocyclops genera share complex evolutionary relationships. This study revealed that the ITS1 and ITS2 regions potentially represent different phylogenetic signals. PMID:25215300
DendroBLAST: approximate phylogenetic trees in the absence of multiple sequence alignments.
Directory of Open Access Journals (Sweden)
Steven Kelly
Full Text Available The rapidly growing availability of genome information has created considerable demand for both fast and accurate phylogenetic inference algorithms. We present a novel method called DendroBLAST for reconstructing phylogenetic dendrograms/trees from protein sequences using BLAST. This method differs from other methods by incorporating a simple model of sequence evolution to test the effect of introducing sequence changes on the reliability of the bipartitions in the inferred tree. Using realistic simulated sequence data we demonstrate that this method produces phylogenetic trees that are more accurate than other commonly-used distance based methods though not as accurate as maximum likelihood methods from good quality multiple sequence alignments. In addition to tests on simulated data, we use DendroBLAST to generate input trees for a supertree reconstruction of the phylogeny of the Archaea. This independent analysis produces an approximate phylogeny of the Archaea that has both high precision and recall when compared to previously published analysis of the same dataset using conventional methods. Taken together these results demonstrate that approximate phylogenetic trees can be produced in the absence of multiple sequence alignments, and we propose that these trees will provide a platform for improving and informing downstream bioinformatic analysis. A web implementation of the DendroBLAST method is freely available for use at http://www.dendroblast.com/.
Lv, Changda; Li, Qi; Kong, Lingfeng
2018-01-01
Mitochondrial genomes have proved to be a powerful tool in resolving phylogenetic relationship. In order to understand the mitogenome characteristics and phylogenetic position of the genus Dosinia, we sequenced the complete mitochondrial genomes of Dosinia altior and Dosinia troscheli (Bivalvia: Veneridae), compared them with that of Dosinia japonica and established a phylogenetic tree for Veneridae. The mitogenomes of D. altior (17,536 bp) and D. troscheli (17,229 bp) are the two smallest in Veneridae, which include 13 protein-coding genes, 2 ribosomal RNA genes, 22 tRNA genes, and non-coding regions. The mitogenomes of the Dosinia species are similar in size, gene content, AT content, AT- and GC- skews, and gene arrangement. The phylogenetic relationships of family Veneridae were established based on 12 concatenated protein-coding genes using maximum likelihood and Bayesian analyses, which supported that Dosininae and Meretricinae have a closer relationship, with Tapetinae being the sister taxon. The information obtained in this study will contribute to further understanding of the molecular features of bivalve mitogenomes and the evolutionary history of the genus Dosinia.
Unrealistic phylogenetic trees may improve phylogenetic footprinting.
Nettling, Martin; Treutler, Hendrik; Cerquides, Jesus; Grosse, Ivo
2017-06-01
The computational investigation of DNA binding motifs from binding sites is one of the classic tasks in bioinformatics and a prerequisite for understanding gene regulation as a whole. Due to the development of sequencing technologies and the increasing number of available genomes, approaches based on phylogenetic footprinting become increasingly attractive. Phylogenetic footprinting requires phylogenetic trees with attached substitution probabilities for quantifying the evolution of binding sites, but these trees and substitution probabilities are typically not known and cannot be estimated easily. Here, we investigate the influence of phylogenetic trees with different substitution probabilities on the classification performance of phylogenetic footprinting using synthetic and real data. For synthetic data we find that the classification performance is highest when the substitution probability used for phylogenetic footprinting is similar to that used for data generation. For real data, however, we typically find that the classification performance of phylogenetic footprinting surprisingly increases with increasing substitution probabilities and is often highest for unrealistically high substitution probabilities close to one. This finding suggests that choosing realistic model assumptions might not always yield optimal predictions in general and that choosing unrealistically high substitution probabilities close to one might actually improve the classification performance of phylogenetic footprinting. The proposed PF is implemented in JAVA and can be downloaded from https://github.com/mgledi/PhyFoo. : martin.nettling@informatik.uni-halle.de. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press.
Extended likelihood inference in reliability
International Nuclear Information System (INIS)
Martz, H.F. Jr.; Beckman, R.J.; Waller, R.A.
1978-10-01
Extended likelihood methods of inference are developed in which subjective information in the form of a prior distribution is combined with sampling results by means of an extended likelihood function. The extended likelihood function is standardized for use in obtaining extended likelihood intervals. Extended likelihood intervals are derived for the mean of a normal distribution with known variance, the failure-rate of an exponential distribution, and the parameter of a binomial distribution. Extended second-order likelihood methods are developed and used to solve several prediction problems associated with the exponential and binomial distributions. In particular, such quantities as the next failure-time, the number of failures in a given time period, and the time required to observe a given number of failures are predicted for the exponential model with a gamma prior distribution on the failure-rate. In addition, six types of life testing experiments are considered. For the binomial model with a beta prior distribution on the probability of nonsurvival, methods are obtained for predicting the number of nonsurvivors in a given sample size and for predicting the required sample size for observing a specified number of nonsurvivors. Examples illustrate each of the methods developed. Finally, comparisons are made with Bayesian intervals in those cases where these are known to exist
Phylogenetic analyses place the monotypic Dryopolystichum within Lomariopsidaceae
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Cheng-Wei Chen
2017-04-01
Full Text Available The monotypic fern genus Dryopolystichum Copel. combines a unique assortment of characters that obscures its relationship to other ferns. Its thin-walled sporangium with a vertical and interrupted annulus, round sorus with peltate indusium, and petiole with several vascular bundles place it in suborder Polypodiineae, but more precise placement has eluded previous authors. Here we investigate its phylogenetic position using three plastid DNA markers, rbcL, rps4-trnS, and trnL-F, and a broad sampling of Polypodiineae. We also provide new data on Dryopolystichum including spore number counts, reproductive mode, spore SEM images, and chromosome counts. Our maximum-likelihood and Bayesian-inference phylogenetic analyses unambiguously place Dryopolystichum within Lomariopsidaceae, a position not previously suggested. Dryopolystichum was resolved as sister to a clade comprising Dracoglossum and Lomariopsis, with Cyclopeltis as sister to these, but clade support is not robust. All examined sporangia of Dryopolystichum produced 32 spores, and the chromosome number of sporophyte somatic cells is ca. 164. Flow cytometric results indicated that the genome size in the spore nuclei is approximately half the size of those from sporophyte leaf tissues, suggesting that Dryopolystichum reproduces sexually. Our findings render Lomariopsidaceae as one of the most morphologically heterogeneous fern families. A recircumscription is provided for both Lomariopsidaceae and Dryopolystichum, and selected characters are briefly discussed considering the newly generated data.
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César da Silva Chagas
2013-04-01
Full Text Available Soil surveys are the main source of spatial information on soils and have a range of different applications, mainly in agriculture. The continuity of this activity has however been severely compromised, mainly due to a lack of governmental funding. The purpose of this study was to evaluate the feasibility of two different classifiers (artificial neural networks and a maximum likelihood algorithm in the prediction of soil classes in the northwest of the state of Rio de Janeiro. Terrain attributes such as elevation, slope, aspect, plan curvature and compound topographic index (CTI and indices of clay minerals, iron oxide and Normalized Difference Vegetation Index (NDVI, derived from Landsat 7 ETM+ sensor imagery, were used as discriminating variables. The two classifiers were trained and validated for each soil class using 300 and 150 samples respectively, representing the characteristics of these classes in terms of the discriminating variables. According to the statistical tests, the accuracy of the classifier based on artificial neural networks (ANNs was greater than of the classic Maximum Likelihood Classifier (MLC. Comparing the results with 126 points of reference showed that the resulting ANN map (73.81 % was superior to the MLC map (57.94 %. The main errors when using the two classifiers were caused by: a the geological heterogeneity of the area coupled with problems related to the geological map; b the depth of lithic contact and/or rock exposure, and c problems with the environmental correlation model used due to the polygenetic nature of the soils. This study confirms that the use of terrain attributes together with remote sensing data by an ANN approach can be a tool to facilitate soil mapping in Brazil, primarily due to the availability of low-cost remote sensing data and the ease by which terrain attributes can be obtained.O levantamento de solos é a principal fonte de informação espacial sobre solos para diferentes usos
On the likelihood function of Gaussian max-stable processes
Genton, M. G.; Ma, Y.; Sang, H.
2011-01-01
We derive a closed form expression for the likelihood function of a Gaussian max-stable process indexed by ℝd at p≤d+1 sites, d≥1. We demonstrate the gain in efficiency in the maximum composite likelihood estimators of the covariance matrix from p=2 to p=3 sites in ℝ2 by means of a Monte Carlo simulation study. © 2011 Biometrika Trust.
On the likelihood function of Gaussian max-stable processes
Genton, M. G.
2011-05-24
We derive a closed form expression for the likelihood function of a Gaussian max-stable process indexed by ℝd at p≤d+1 sites, d≥1. We demonstrate the gain in efficiency in the maximum composite likelihood estimators of the covariance matrix from p=2 to p=3 sites in ℝ2 by means of a Monte Carlo simulation study. © 2011 Biometrika Trust.
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Dandekar Thomas
2010-01-01
Full Text Available Abstract Background In several studies, secondary structures of ribosomal genes have been used to improve the quality of phylogenetic reconstructions. An extensive evaluation of the benefits of secondary structure, however, is lacking. Results This is the first study to counter this deficiency. We inspected the accuracy and robustness of phylogenetics with individual secondary structures by simulation experiments for artificial tree topologies with up to 18 taxa and for divergency levels in the range of typical phylogenetic studies. We chose the internal transcribed spacer 2 of the ribosomal cistron as an exemplary marker region. Simulation integrated the coevolution process of sequences with secondary structures. Additionally, the phylogenetic power of marker size duplication was investigated and compared with sequence and sequence-structure reconstruction methods. The results clearly show that accuracy and robustness of Neighbor Joining trees are largely improved by structural information in contrast to sequence only data, whereas a doubled marker size only accounts for robustness. Conclusions Individual secondary structures of ribosomal RNA sequences provide a valuable gain of information content that is useful for phylogenetics. Thus, the usage of ITS2 sequence together with secondary structure for taxonomic inferences is recommended. Other reconstruction methods as maximum likelihood, bayesian inference or maximum parsimony may equally profit from secondary structure inclusion. Reviewers This article was reviewed by Shamil Sunyaev, Andrea Tanzer (nominated by Frank Eisenhaber and Eugene V. Koonin. Open peer review Reviewed by Shamil Sunyaev, Andrea Tanzer (nominated by Frank Eisenhaber and Eugene V. Koonin. For the full reviews, please go to the Reviewers' comments section.
Malyarchuk, Boris; Derenko, Miroslava; Mikhailova, Ekaterina; Denisova, Galina
2014-02-01
Phylogenetic and statistical analyses of DNA sequences of two genes, cytochrome oxidase subunit 1 (cox 1) of the mitochondrial DNA and 18S subunit of the nuclear ribosomal RNA (18S rRNA), was used to characterize Neoechinorhynchus species from fishes collected in different localities of North-East Asia. It has been found that four species can be clearly recognized using molecular markers-Neoechinorhynchus tumidus, Neoechinorhynchus beringianus, Neoechinorhynchus simansularis and Neoechinorhynchus salmonis. 18S sequences ascribed to Neoechinorhynchus crassus specimens from North-East Asia were identical to those of N. tumidus, but differed substantially from North American N. crassus. We renamed North-East Asian N. crassus specimens to N. sp., although the possibility that they represent a subspecies of N. tumidus cannot be excluded, taking into account a relatively small distance between cox 1 sequences of North-East Asian specimens of N. crassus and N. tumidus. Maximum likelihood, maximum parsimony and Bayesian inference analyses were performed for phylogeny reconstruction. All the phylogenetic trees showed that North-East Asian species of Neoechinorhynchus analyzed in this study represent independent clades, with the only exception of N. tumidus and N. sp. for 18S data. Phylogenetic analysis has shown that the majority of species sampled (N. tumidus+N. sp., N. simansularis and N. beringianus) are probably very closely related, while N. salmonis occupies separate position in the trees, possibly indicating a North American origin of this species. © 2013.
Unbinned likelihood analysis of EGRET observations
International Nuclear Information System (INIS)
Digel, Seth W.
2000-01-01
We present a newly-developed likelihood analysis method for EGRET data that defines the likelihood function without binning the photon data or averaging the instrumental response functions. The standard likelihood analysis applied to EGRET data requires the photons to be binned spatially and in energy, and the point-spread functions to be averaged over energy and inclination angle. The full-width half maximum of the point-spread function increases by about 40% from on-axis to 30 degree sign inclination, and depending on the binning in energy can vary by more than that in a single energy bin. The new unbinned method avoids the loss of information that binning and averaging cause and can properly analyze regions where EGRET viewing periods overlap and photons with different inclination angles would otherwise be combined in the same bin. In the poster, we describe the unbinned analysis method and compare its sensitivity with binned analysis for detecting point sources in EGRET data
A simulation study of likelihood inference procedures in rayleigh distribution with censored data
International Nuclear Information System (INIS)
Baklizi, S. A.; Baker, H. M.
2001-01-01
Inference procedures based on the likelihood function are considered for the one parameter Rayleigh distribution with type1 and type 2 censored data. Using simulation techniques, the finite sample performances of the maximum likelihood estimator and the large sample likelihood interval estimation procedures based on the Wald, the Rao, and the likelihood ratio statistics are investigated. It appears that the maximum likelihood estimator is unbiased. The approximate variance estimates obtained from the asymptotic normal distribution of the maximum likelihood estimator are accurate under type 2 censored data while they tend to be smaller than the actual variances when considering type1 censored data of small size. It appears also that interval estimation based on the Wald and Rao statistics need much more sample size than interval estimation based on the likelihood ratio statistic to attain reasonable accuracy. (authors). 15 refs., 4 tabs
Subbotin, S A; Vierstraete, A; De Ley, P; Rowe, J; Waeyenberge, L; Moens, M; Vanfleteren, J R
2001-10-01
The ITS1, ITS2, and 5.8S gene sequences of nuclear ribosomal DNA from 40 taxa of the family Heteroderidae (including the genera Afenestrata, Cactodera, Heterodera, Globodera, Punctodera, Meloidodera, Cryphodera, and Thecavermiculatus) were sequenced and analyzed. The ITS regions displayed high levels of sequence divergence within Heteroderinae and compared to outgroup taxa. Unlike recent findings in root knot nematodes, ITS sequence polymorphism does not appear to complicate phylogenetic analysis of cyst nematodes. Phylogenetic analyses with maximum-parsimony, minimum-evolution, and maximum-likelihood methods were performed with a range of computer alignments, including elision and culled alignments. All multiple alignments and phylogenetic methods yielded similar basic structure for phylogenetic relationships of Heteroderidae. The cyst-forming nematodes are represented by six main clades corresponding to morphological characters and host specialization, with certain clades assuming different positions depending on alignment procedure and/or method of phylogenetic inference. Hypotheses of monophyly of Punctoderinae and Heteroderinae are, respectively, strongly and moderately supported by the ITS data across most alignments. Close relationships were revealed between the Avenae and the Sacchari groups and between the Humuli group and the species H. salixophila within Heteroderinae. The Goettingiana group occupies a basal position within this subfamily. The validity of the genera Afenestrata and Bidera was tested and is discussed based on molecular data. We conclude that ITS sequence data are appropriate for studies of relationships within the different species groups and less so for recovery of more ancient speciations within Heteroderidae. Copyright 2001 Academic Press.
Obtaining reliable Likelihood Ratio tests from simulated likelihood functions
DEFF Research Database (Denmark)
Andersen, Laura Mørch
It is standard practice by researchers and the default option in many statistical programs to base test statistics for mixed models on simulations using asymmetric draws (e.g. Halton draws). This paper shows that when the estimated likelihood functions depend on standard deviations of mixed param...
Long-branch attraction bias and inconsistency in Bayesian phylogenetics.
Kolaczkowski, Bryan; Thornton, Joseph W
2009-12-09
Bayesian inference (BI) of phylogenetic relationships uses the same probabilistic models of evolution as its precursor maximum likelihood (ML), so BI has generally been assumed to share ML's desirable statistical properties, such as largely unbiased inference of topology given an accurate model and increasingly reliable inferences as the amount of data increases. Here we show that BI, unlike ML, is biased in favor of topologies that group long branches together, even when the true model and prior distributions of evolutionary parameters over a group of phylogenies are known. Using experimental simulation studies and numerical and mathematical analyses, we show that this bias becomes more severe as more data are analyzed, causing BI to infer an incorrect tree as the maximum a posteriori phylogeny with asymptotically high support as sequence length approaches infinity. BI's long branch attraction bias is relatively weak when the true model is simple but becomes pronounced when sequence sites evolve heterogeneously, even when this complexity is incorporated in the model. This bias--which is apparent under both controlled simulation conditions and in analyses of empirical sequence data--also makes BI less efficient and less robust to the use of an incorrect evolutionary model than ML. Surprisingly, BI's bias is caused by one of the method's stated advantages--that it incorporates uncertainty about branch lengths by integrating over a distribution of possible values instead of estimating them from the data, as ML does. Our findings suggest that trees inferred using BI should be interpreted with caution and that ML may be a more reliable framework for modern phylogenetic analysis.
Long-branch attraction bias and inconsistency in Bayesian phylogenetics.
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Bryan Kolaczkowski
Full Text Available Bayesian inference (BI of phylogenetic relationships uses the same probabilistic models of evolution as its precursor maximum likelihood (ML, so BI has generally been assumed to share ML's desirable statistical properties, such as largely unbiased inference of topology given an accurate model and increasingly reliable inferences as the amount of data increases. Here we show that BI, unlike ML, is biased in favor of topologies that group long branches together, even when the true model and prior distributions of evolutionary parameters over a group of phylogenies are known. Using experimental simulation studies and numerical and mathematical analyses, we show that this bias becomes more severe as more data are analyzed, causing BI to infer an incorrect tree as the maximum a posteriori phylogeny with asymptotically high support as sequence length approaches infinity. BI's long branch attraction bias is relatively weak when the true model is simple but becomes pronounced when sequence sites evolve heterogeneously, even when this complexity is incorporated in the model. This bias--which is apparent under both controlled simulation conditions and in analyses of empirical sequence data--also makes BI less efficient and less robust to the use of an incorrect evolutionary model than ML. Surprisingly, BI's bias is caused by one of the method's stated advantages--that it incorporates uncertainty about branch lengths by integrating over a distribution of possible values instead of estimating them from the data, as ML does. Our findings suggest that trees inferred using BI should be interpreted with caution and that ML may be a more reliable framework for modern phylogenetic analysis.
Naushad, Sohail; Barkema, Herman W.; Luby, Christopher; Condas, Larissa A. Z.; Nobrega, Diego B.; Carson, Domonique A.; De Buck, Jeroen
2016-01-01
Non-aureus staphylococci (NAS), a heterogeneous group of a large number of species and subspecies, are the most frequently isolated pathogens from intramammary infections in dairy cattle. Phylogenetic relationships among bovine NAS species are controversial and have mostly been determined based on single-gene trees. Herein, we analyzed phylogeny of bovine NAS species using whole-genome sequencing (WGS) of 441 distinct isolates. In addition, evolutionary relationships among bovine NAS were estimated from multilocus data of 16S rRNA, hsp60, rpoB, sodA, and tuf genes and sequences from these and numerous other single genes/proteins. All phylogenies were created with FastTree, Maximum-Likelihood, Maximum-Parsimony, and Neighbor-Joining methods. Regardless of methodology, WGS-trees clearly separated bovine NAS species into five monophyletic coherent clades. Furthermore, there were consistent interspecies relationships within clades in all WGS phylogenetic reconstructions. Except for the Maximum-Parsimony tree, multilocus data analysis similarly produced five clades. There were large variations in determining clades and interspecies relationships in single gene/protein trees, under different methods of tree constructions, highlighting limitations of using single genes for determining bovine NAS phylogeny. However, based on WGS data, we established a robust phylogeny of bovine NAS species, unaffected by method or model of evolutionary reconstructions. Therefore, it is now possible to determine associations between phylogeny and many biological traits, such as virulence, antimicrobial resistance, environmental niche, geographical distribution, and host specificity. PMID:28066335
Practical likelihood analysis for spatial generalized linear mixed models
DEFF Research Database (Denmark)
Bonat, W. H.; Ribeiro, Paulo Justiniano
2016-01-01
We investigate an algorithm for maximum likelihood estimation of spatial generalized linear mixed models based on the Laplace approximation. We compare our algorithm with a set of alternative approaches for two datasets from the literature. The Rhizoctonia root rot and the Rongelap are......, respectively, examples of binomial and count datasets modeled by spatial generalized linear mixed models. Our results show that the Laplace approximation provides similar estimates to Markov Chain Monte Carlo likelihood, Monte Carlo expectation maximization, and modified Laplace approximation. Some advantages...... of Laplace approximation include the computation of the maximized log-likelihood value, which can be used for model selection and tests, and the possibility to obtain realistic confidence intervals for model parameters based on profile likelihoods. The Laplace approximation also avoids the tuning...
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Mingsheng Yang
2015-03-01
Full Text Available Satyrinae is one of twelve subfamilies of the butterfly family Nymphalidae, which currently includes nine tribes. However, phylogenetic relationships among them remain largely unresolved, though different researches have been conducted based on both morphological and molecular data. However, ribosomal genes have never been used in tribe level phylogenetic analyses of Satyrinae. In this study we investigate for the first time the phylogenetic relationships among the tribes Elymniini, Amathusiini, Zetherini and Melanitini which are indicated to be a monophyletic group, and the Satyrini, using two ribosomal genes (28s rDNA and 16s rDNA and four protein-coding genes (EF-1α, COI, COII and Cytb. We mainly aim to assess the phylogenetic informativeness of the ribosomal genes as well as clarify the relationships among different tribes. Our results show the two ribosomal genes generally have the same high phylogenetic informativeness compared with EF-1α; and we infer the 28s rDNA would show better informativeness if the 28s rDNA sequence data for each sampling taxon are obtained in this study. The placement of the monotypic genus Callarge Leech in Zetherini is confirmed for the first time based on molecular evidence. In addition, our maximum likelihood (ML and Bayesian inference (BI trees consistently show that the involved Satyrinae including the Amathusiini is monophyletic with high support values. Although the relationships among the five tribes are identical among ML and BI analyses and are mostly strongly-supported in BI analysis, those in ML analysis are lowly- or moderately- supported. Therefore, the relationships among the related five tribes recovered herein need further verification based on more sampling taxa.
LIKELIHOOD ESTIMATION OF PARAMETERS USING SIMULTANEOUSLY MONITORED PROCESSES
DEFF Research Database (Denmark)
Friis-Hansen, Peter; Ditlevsen, Ove Dalager
2004-01-01
The topic is maximum likelihood inference from several simultaneously monitored response processes of a structure to obtain knowledge about the parameters of other not monitored but important response processes when the structure is subject to some Gaussian load field in space and time. The consi....... The considered example is a ship sailing with a given speed through a Gaussian wave field....
Ego involvement increases doping likelihood.
Ring, Christopher; Kavussanu, Maria
2018-08-01
Achievement goal theory provides a framework to help understand how individuals behave in achievement contexts, such as sport. Evidence concerning the role of motivation in the decision to use banned performance enhancing substances (i.e., doping) is equivocal on this issue. The extant literature shows that dispositional goal orientation has been weakly and inconsistently associated with doping intention and use. It is possible that goal involvement, which describes the situational motivational state, is a stronger determinant of doping intention. Accordingly, the current study used an experimental design to examine the effects of goal involvement, manipulated using direct instructions and reflective writing, on doping likelihood in hypothetical situations in college athletes. The ego-involving goal increased doping likelihood compared to no goal and a task-involving goal. The present findings provide the first evidence that ego involvement can sway the decision to use doping to improve athletic performance.
Weisrock, David W; Macey, J Robert; Matsui, Masafumi; Mulcahy, Daniel G; Papenfuss, Theodore J
2013-01-01
The salamander family Hynobiidae contains over 50 species and has been the subject of a number of molecular phylogenetic investigations aimed at reconstructing branches across the entire family. In general, studies using the greatest amount of sequence data have used reduced taxon sampling, while the study with the greatest taxon sampling has used a limited sequence data set. Here, we provide insights into the phylogenetic history of the Hynobiidae using both dense taxon sampling and a large mitochondrial DNA sequence data set. We report exclusive new mitochondrial DNA data of 2566 aligned bases (with 151 excluded sites, of included sites 1157 are variable with 957 parsimony informative). This is sampled from two genic regions encoding a 12S-16S region (the 3' end of 12S rRNA, tRNA(VAI), and the 5' end of 16S rRNA), and a ND2-COI region (ND2, tRNA(Trp), tRNA(Ala), tRNA(Asn), the origin for light strand replication--O(L), tRNA(Cys), tRNAT(Tyr), and the 5' end of COI). Analyses using parsimony, Bayesian, and maximum likelihood optimality criteria produce similar phylogenetic trees, with discordant branches generally receiving low levels of branch support. Monophyly of the Hynobiidae is strongly supported across all analyses, as is the sister relationship and deep divergence between the genus Onychodactylus with all remaining hynobiids. Within this latter grouping our phylogenetic results identify six clades that are relatively divergent from one another, but for which there is minimal support for their phylogenetic placement. This includes the genus Batrachuperus, the genus Hynobius, the genus Pachyhynobius, the genus Salamandrella, a clade containing the genera Ranodon and Paradactylodon, and a clade containing the genera Liua and Pseudohynobius. This latter clade receives low bootstrap support in the parsimony analysis, but is consistent across all three analytical methods. Our results also clarify a number of well-supported relationships within the larger
Phylogenetic trends in phenolic metabolism of milkweeds (Asclepias): evidence for escalation.
Agrawal, Anurag A; Salminen, Juha-Pekka; Fishbein, Mark
2009-03-01
Although plant-defense theory has long predicted patterns of chemical defense across taxa, we know remarkably little about the evolution of defense, especially in the context of directional phylogenetic trends. Here we contrast the production of phenolics and cardenolides in 35 species of milkweeds (Asclepias and Gomphocarpus). Maximum-likelihood analyses of character evolution revealed three major patterns. First, consistent with the defense-escalation hypothesis, the diversification of the milkweeds was associated with a trend for increasing phenolic production; this pattern was reversed (a declining evolutionary trend) for cardenolides, toxins sequestered by specialist herbivores. Second, phylogenetically independent correlations existed among phenolic classes across species. For example, coumaric acid derivatives showed negatively correlated evolution with caffeic acid derivatives, and this was likely driven by the fact that the former are used as precursors for the latter. In contrast, coumaric acid derivatives were positively correlated with flavonoids, consistent with competition for the precursor p-coumaric acid. Finally, of the phenolic classes, only flavonoids showed correlated evolution (positive) with cardenolides, consistent with a physiological and evolutionary link between the two via malonate. Thus, this study presents a rigorous test of the defense-escalation hypothesis and a novel phylogenetic approach to understanding the long-term persistence of physiological constraints on secondary metabolism.
Sun, Xiaomin; Zhao, Ruoping; Zhang, Ting; Gong, Jie; Jing, Meidong; Huang, Ling
2017-10-01
Coraciiformes comprises 209 species belonging to ten families with significant divergence on external morphologies and life styles. The phylogenetic placement of Coraciiformes was still in debate. Here, we determined the complete mitochondrial genomes (mitogenomes) of Crested Kingfisher (Ceryle rudis) and Black-capped Kingfisher (Halcyon pileata). The mitogenomes were 17,355 bp (C. rudis) and 17,612 bp (H. pileata) in length, and both of them contained 37 genes (two rRNA genes, 22 tRNA genes and 13 protein-coding genes) and one control region. The gene organizations and characters of two mitogenomes were similar with those of other mitogenomes in Coraciiformes, however the sizes and nucleotide composition of control regions in different mitogenomes were significantly different. Phylogenetic trees were constructed with both Bayesian and Maximum Likelihood methods based on mitogenome sequences from 11 families of six orders. The trees based on two different data sets supported the basal position of Psittacidae (Psittaciformes), the closest relationship between Cuculiformes (Cuculidae) and Trogoniformes (Trogonidae), and the close relationship between Coraciiformes and Piciformes. The phylogenetic placement of the clade including Cuculiformes and Trogoniformes has not been resolved in present study, which need further investigations with more molecular markers and species. The mitogenome sequences presented here provided valuable data for further taxonomic studies on Coraciiformes and other related groups.
Buckley, Thomas R; James, Sam; Allwood, Julia; Bartlam, Scott; Howitt, Robyn; Prada, Diana
2011-01-01
We have constructed the first ever phylogeny for the New Zealand earthworm fauna (Megascolecinae and Acanthodrilinae) including representatives from other major continental regions. Bayesian and maximum likelihood phylogenetic trees were constructed from 427 base pairs from the mitochondrial large subunit (16S) rRNA gene and 661 base pairs from the nuclear large subunit (28S) rRNA gene. Within the Acanthodrilinae we were able to identify a number of well-supported clades that were restricted to continental landmasses. Estimates of nodal support for these major clades were generally high, but relationships among clades were poorly resolved. The phylogenetic analyses revealed several independent lineages in New Zealand, some of which had a comparable phylogenetic depth to monophyletic groups sampled from Madagascar, Africa, North America and Australia. These results are consistent with at least some of these clades having inhabited New Zealand since rifting from Gondwana in the Late Cretaceous. Within the New Zealand Acanthodrilinae, major clades tended to be restricted to specific regions of New Zealand, with the central North Island and Cook Strait representing major biogeographic boundaries. Our field surveys of New Zealand and subsequent identification has also revealed extensive cryptic taxonomic diversity with approximately 48 new species sampled in addition to the 199 species recognized by previous authors. Our results indicate that further survey and taxonomic work is required to establish a foundation for future biogeographic and ecological research on this vitally important component of the New Zealand biota. Copyright © 2010 Elsevier Inc. All rights reserved.
McCann, Jamie; Schneeweiss, Gerald M; Stuessy, Tod F; Villaseñor, Jose L; Weiss-Schneeweiss, Hanna
2016-01-01
Chromosome number change (polyploidy and dysploidy) plays an important role in plant diversification and speciation. Investigating chromosome number evolution commonly entails ancestral state reconstruction performed within a phylogenetic framework, which is, however, prone to uncertainty, whose effects on evolutionary inferences are insufficiently understood. Using the chromosomally diverse plant genus Melampodium (Asteraceae) as model group, we assess the impact of reconstruction method (maximum parsimony, maximum likelihood, Bayesian methods), branch length model (phylograms versus chronograms) and phylogenetic uncertainty (topological and branch length uncertainty) on the inference of chromosome number evolution. We also address the suitability of the maximum clade credibility (MCC) tree as single representative topology for chromosome number reconstruction. Each of the listed factors causes considerable incongruence among chromosome number reconstructions. Discrepancies between inferences on the MCC tree from those made by integrating over a set of trees are moderate for ancestral chromosome numbers, but severe for the difference of chromosome gains and losses, a measure of the directionality of dysploidy. Therefore, reliance on single trees, such as the MCC tree, is strongly discouraged and model averaging, taking both phylogenetic and model uncertainty into account, is recommended. For studying chromosome number evolution, dedicated models implemented in the program ChromEvol and ordered maximum parsimony may be most appropriate. Chromosome number evolution in Melampodium follows a pattern of bidirectional dysploidy (starting from x = 11 to x = 9 and x = 14, respectively) with no prevailing direction.
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Jamie McCann
Full Text Available Chromosome number change (polyploidy and dysploidy plays an important role in plant diversification and speciation. Investigating chromosome number evolution commonly entails ancestral state reconstruction performed within a phylogenetic framework, which is, however, prone to uncertainty, whose effects on evolutionary inferences are insufficiently understood. Using the chromosomally diverse plant genus Melampodium (Asteraceae as model group, we assess the impact of reconstruction method (maximum parsimony, maximum likelihood, Bayesian methods, branch length model (phylograms versus chronograms and phylogenetic uncertainty (topological and branch length uncertainty on the inference of chromosome number evolution. We also address the suitability of the maximum clade credibility (MCC tree as single representative topology for chromosome number reconstruction. Each of the listed factors causes considerable incongruence among chromosome number reconstructions. Discrepancies between inferences on the MCC tree from those made by integrating over a set of trees are moderate for ancestral chromosome numbers, but severe for the difference of chromosome gains and losses, a measure of the directionality of dysploidy. Therefore, reliance on single trees, such as the MCC tree, is strongly discouraged and model averaging, taking both phylogenetic and model uncertainty into account, is recommended. For studying chromosome number evolution, dedicated models implemented in the program ChromEvol and ordered maximum parsimony may be most appropriate. Chromosome number evolution in Melampodium follows a pattern of bidirectional dysploidy (starting from x = 11 to x = 9 and x = 14, respectively with no prevailing direction.
Monogenean anchor morphometry: systematic value, phylogenetic signal, and evolution
Soo, Oi Yoon Michelle; Tan, Wooi Boon; Lim, Lee Hong Susan
2016-01-01
Background. Anchors are one of the important attachment appendages for monogenean parasites. Common descent and evolutionary processes have left their mark on anchor morphometry, in the form of patterns of shape and size variation useful for systematic and evolutionary studies. When combined with morphological and molecular data, analysis of anchor morphometry can potentially answer a wide range of biological questions. Materials and Methods. We used data from anchor morphometry, body size and morphology of 13 Ligophorus (Monogenea: Ancyrocephalidae) species infecting two marine mugilid (Teleostei: Mugilidae) fish hosts: Moolgarda buchanani (Bleeker) and Liza subviridis (Valenciennes) from Malaysia. Anchor shape and size data (n = 530) were generated using methods of geometric morphometrics. We used 28S rRNA, 18S rRNA, and ITS1 sequence data to infer a maximum likelihood phylogeny. We discriminated species using principal component and cluster analysis of shape data. Adams’s Kmult was used to detect phylogenetic signal in anchor shape. Phylogeny-correlated size and shape changes were investigated using continuous character mapping and directional statistics, respectively. We assessed morphological constraints in anchor morphometry using phylogenetic regression of anchor shape against body size and anchor size. Anchor morphological integration was studied using partial least squares method. The association between copulatory organ morphology and anchor shape and size in phylomorphospace was used to test the Rohde-Hobbs hypothesis. We created monogeneaGM, a new R package that integrates analyses of monogenean anchor geometric morphometric data with morphological and phylogenetic data. Results. We discriminated 12 of the 13 Ligophorus species using anchor shape data. Significant phylogenetic signal was detected in anchor shape. Thus, we discovered new morphological characters based on anchor shaft shape, the length between the inner root point and the outer root
Fast algorithms for computing phylogenetic divergence time.
Crosby, Ralph W; Williams, Tiffani L
2017-12-06
The inference of species divergence time is a key step in most phylogenetic studies. Methods have been available for the last ten years to perform the inference, but the performance of the methods does not yet scale well to studies with hundreds of taxa and thousands of DNA base pairs. For example a study of 349 primate taxa was estimated to require over 9 months of processing time. In this work, we present a new algorithm, AncestralAge, that significantly improves the performance of the divergence time process. As part of AncestralAge, we demonstrate a new method for the computation of phylogenetic likelihood and our experiments show a 90% improvement in likelihood computation time on the aforementioned dataset of 349 primates taxa with over 60,000 DNA base pairs. Additionally, we show that our new method for the computation of the Bayesian prior on node ages reduces the running time for this computation on the 349 taxa dataset by 99%. Through the use of these new algorithms we open up the ability to perform divergence time inference on large phylogenetic studies.
Reeb, Valérie; Lutzoni, François; Roux, Claude
2004-09-01
Despite the recent progress in molecular phylogenetics, many of the deepest relationships among the main lineages of the largest fungal phylum, Ascomycota, remain unresolved. To increase both resolution and support on a large-scale phylogeny of lichenized and non-lichenized ascomycetes, we combined the protein coding-gene RPB2 with the traditionally used nuclear ribosomal genes SSU and LSU. Our analyses resulted in the naming of the new subclasses Acarosporomycetidae and Ostropomycetidae, and the new class Lichinomycetes, as well as the establishment of the phylogenetic placement and novel circumscription of the lichen-forming fungi family Acarosporaceae. The delimitation of this family has been problematic over the past century, because its main diagnostic feature, true polyspory (numerous spores issued from multiple post-meiosis mitoses) with over 100 spores per ascus, is probably not restricted to the Acarosporaceae. This observation was confirmed by our reconstruction of the origin and evolution of this form of true polyspory using maximum likelihood as the optimality criterion. The various phylogenetic analyses carried out on our data sets allowed us to conclude that: (1) the inclusion of phylogenetic signal from ambiguously aligned regions into the maximum parsimony analyses proved advantageous in reconstructing phylogeny; however, when more data become available, Bayesian analysis using different models of evolution is likely to be more efficient; (2) neighbor-joining bootstrap proportions seem to be more appropriate in detecting topological conflict between data partitions of large-scale phylogenies than posterior probabilities; and (3) Bayesian bootstrap proportion provides a compromise between posterior probability outcomes (i.e., higher accuracy, but with a higher number of significantly supported wrong internodes) vs. maximum likelihood bootstrap proportion outcomes (i.e., lower accuracy, with a lower number of significantly supported wrong internodes).
Likelihood estimators for multivariate extremes
Huser, Raphaë l; Davison, Anthony C.; Genton, Marc G.
2015-01-01
The main approach to inference for multivariate extremes consists in approximating the joint upper tail of the observations by a parametric family arising in the limit for extreme events. The latter may be expressed in terms of componentwise maxima, high threshold exceedances or point processes, yielding different but related asymptotic characterizations and estimators. The present paper clarifies the connections between the main likelihood estimators, and assesses their practical performance. We investigate their ability to estimate the extremal dependence structure and to predict future extremes, using exact calculations and simulation, in the case of the logistic model.
Likelihood estimators for multivariate extremes
Huser, Raphaël
2015-11-17
The main approach to inference for multivariate extremes consists in approximating the joint upper tail of the observations by a parametric family arising in the limit for extreme events. The latter may be expressed in terms of componentwise maxima, high threshold exceedances or point processes, yielding different but related asymptotic characterizations and estimators. The present paper clarifies the connections between the main likelihood estimators, and assesses their practical performance. We investigate their ability to estimate the extremal dependence structure and to predict future extremes, using exact calculations and simulation, in the case of the logistic model.
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Min Chen
Full Text Available To investigate the linkage of HIV transmission from a man to a woman through unprotected sexual contact without disclosing his HIV-positive status.Combined with epidemiological information and serological tests, phylogenetic analysis was used to test the a priori hypothesis of HIV transmission from the man to the woman. Control subjects, infected with HIV through heterosexual intercourse, from the same location were also sampled. Phylogenetic analyses were performed using the consensus gag, pol and env sequences obtained from blood samples of the man, the woman and the local control subjects. The env quasispecies of the man, the woman, and two controls were also obtained using single genome amplification and sequencing (SGA/S to explore the paraphyletic relationship by phylogenetic analysis.Epidemiological information and serological tests indicated that the man was infected with HIV-1 earlier than the woman. Phylogenetic analyses of the consensus sequences showed a monophyletic cluster for the man and woman in all three genomic regions. Furthermore, gag sequences of the man and woman shared a unique recombination pattern from subtype B and C, which was different from those of CRF07_BC or CRF08_BC observed in the local samples. These indicated that the viral sequences from the two subjects display a high level of similarity. Further, viral quasispecies from the man exhibited a paraphyletic relationship with those from the woman in the Bayesian and maximum-likelihood (ML phylogenetic trees of the env region, which supported the transmission direction from the man to the woman.In the context of epidemiological and serological evidence, the results of phylogenetic analyses support the transmission from the man to the woman.
Kim, Man Il; Wan, Xinlong; Kim, Min Jee; Jeong, Heon Cheon; Ahn, Neung-Ho; Kim, Ki-Gyoung; Han, Yeon Soo; Kim, Iksoo
2010-11-01
The molecular phylogenetic relationships among true butterfly families (superfamily Papilionoidea) have been a matter of substantial controversy; this debate has led to several competing hypotheses. Two of the most compelling of those hypotheses involve the relationships of (Nymphalidae + Lycaenidae) + (Pieridae + Papilionidae) and (((Nymphalidae + Lycaenidae) + Pieridae) + Papilionidae). In this study, approximately 3,500 nucleotide sequences from cytochrome oxidase subunit I (COI), 16S ribosomal RNA (16S rRNA), and elongation factor-1 alpha (EF-1α) were sequenced from 83 species belonging to four true butterfly families, along with those of three outgroup species belonging to three lepidopteran superfamilies. These sequences were subjected to phylogenetic reconstruction via Bayesian Inference (BI), Maximum Likelihood (ML), and Maximum Parsimony (MP) algorithms. The monophyletic Pieridae and monophyletic Papilionidae evidenced good recovery in all analyses, but in some analyses, the monophylies of the Lycaenidae and Nymphalidae were hampered by the inclusion of single species of the lycaenid subfamily Miletinae and the nymphalid subfamily Danainae. Excluding those singletons, all phylogenetic analyses among the four true butterfly families clearly identified the Nymphalidae as the sister to the Lycaenidae and identified this group as a sister to the Pieridae, with the Papilionidae identified as the most basal linage to the true butterfly, thus supporting the hypothesis: (Papilionidae + (Pieridae + (Nymphalidae + Lycaenidae))).
A note on estimating errors from the likelihood function
International Nuclear Information System (INIS)
Barlow, Roger
2005-01-01
The points at which the log likelihood falls by 12 from its maximum value are often used to give the 'errors' on a result, i.e. the 68% central confidence interval. The validity of this is examined for two simple cases: a lifetime measurement and a Poisson measurement. Results are compared with the exact Neyman construction and with the simple Bartlett approximation. It is shown that the accuracy of the log likelihood method is poor, and the Bartlett construction explains why it is flawed
Speiser, Daniel I; Pankey, M Sabrina; Zaharoff, Alexander K; Battelle, Barbara A; Bracken-Grissom, Heather D; Breinholt, Jesse W; Bybee, Seth M; Cronin, Thomas W; Garm, Anders; Lindgren, Annie R; Patel, Nipam H; Porter, Megan L; Protas, Meredith E; Rivera, Ajna S; Serb, Jeanne M; Zigler, Kirk S; Crandall, Keith A; Oakley, Todd H
2014-11-19
Tools for high throughput sequencing and de novo assembly make the analysis of transcriptomes (i.e. the suite of genes expressed in a tissue) feasible for almost any organism. Yet a challenge for biologists is that it can be difficult to assign identities to gene sequences, especially from non-model organisms. Phylogenetic analyses are one useful method for assigning identities to these sequences, but such methods tend to be time-consuming because of the need to re-calculate trees for every gene of interest and each time a new data set is analyzed. In response, we employed existing tools for phylogenetic analysis to produce a computationally efficient, tree-based approach for annotating transcriptomes or new genomes that we term Phylogenetically-Informed Annotation (PIA), which places uncharacterized genes into pre-calculated phylogenies of gene families. We generated maximum likelihood trees for 109 genes from a Light Interaction Toolkit (LIT), a collection of genes that underlie the function or development of light-interacting structures in metazoans. To do so, we searched protein sequences predicted from 29 fully-sequenced genomes and built trees using tools for phylogenetic analysis in the Osiris package of Galaxy (an open-source workflow management system). Next, to rapidly annotate transcriptomes from organisms that lack sequenced genomes, we repurposed a maximum likelihood-based Evolutionary Placement Algorithm (implemented in RAxML) to place sequences of potential LIT genes on to our pre-calculated gene trees. Finally, we implemented PIA in Galaxy and used it to search for LIT genes in 28 newly-sequenced transcriptomes from the light-interacting tissues of a range of cephalopod mollusks, arthropods, and cubozoan cnidarians. Our new trees for LIT genes are available on the Bitbucket public repository ( http://bitbucket.org/osiris_phylogenetics/pia/ ) and we demonstrate PIA on a publicly-accessible web server ( http://galaxy-dev.cnsi.ucsb.edu/pia/ ). Our new
López-Wilchis, Ricardo; Del Río-Portilla, Miguel Ángel; Guevara-Chumacero, Luis Manuel
2017-02-01
We described the complete mitochondrial genome (mitogenome) of the Wagner's mustached bat, Pteronotus personatus, a species belonging to the family Mormoopidae, and compared it with other published mitogenomes of bats (Chiroptera). The mitogenome of P. personatus was 16,570 bp long and contained a typically conserved structure including 13 protein-coding genes, 22 transfer RNA genes, two ribosomal RNA genes, and one control region (D-loop). Most of the genes were encoded on the H-strand, except for eight tRNA and the ND6 genes. The order of protein-coding and rRNA genes was highly conserved in all mitogenomes. All protein-coding genes started with an ATG codon, except for ND2, ND3, and ND5, which initiated with ATA, and terminated with the typical stop codon TAA/TAG or the codon AGA. Phylogenetic trees constructed using Maximum Parsimony, Maximum Likelihood, and Bayesian inference methods showed an identical topology and indicated the monophyly of different families of bats (Mormoopidae, Phyllostomidae, Vespertilionidae, Rhinolophidae, and Pteropopidae) and the existence of two major clades corresponding to the suborders Yangochiroptera and Yinpterochiroptera. The mitogenome sequence provided here will be useful for further phylogenetic analyses and population genetic studies in mormoopid bats.
Phylogenetic study of Class Armophorea (Alveolata, Ciliophora based on 18S-rDNA data
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Thiago da Silva Paiva
2013-01-01
Full Text Available The 18S rDNA phylogeny of Class Armophorea, a group of anaerobic ciliates, is proposed based on an analysis of 44 sequences (out of 195 retrieved from the NCBI/GenBank database. Emphasis was placed on the use of two nucleotide alignment criteria that involved variation in the gap-opening and gap-extension parameters and the use of rRNA secondary structure to orientate multiple-alignment. A sensitivity analysis of 76 data sets was run to assess the effect of variations in indel parameters on tree topologies. Bayesian inference, maximum likelihood and maximum parsimony phylogenetic analyses were used to explore how different analytic frameworks influenced the resulting hypotheses. A sensitivity analysis revealed that the relationships among higher taxa of the Intramacronucleata were dependent upon how indels were determined during multiple-alignment of nucleotides. The phylogenetic analyses rejected the monophyly of the Armophorea most of the time and consistently indicated that the Metopidae and Nyctotheridae were related to the Litostomatea. There was no consensus on the placement of the Caenomorphidae, which could be a sister group of the Metopidae + Nyctorheridae, or could have diverged at the base of the Spirotrichea branch or the Intramacronucleata tree.
Complex phylogenetic placement of ilex species (aquifoliaceae): a case study of molecular phylogeny
International Nuclear Information System (INIS)
Yi, F.; Sun, L.; Xiao, P.G.; Hao, D.C.
2017-01-01
To investigate the phylogenetic relationships among Ilex species distributed in China, we analyzed two alignments including 4,698 characters corresponding to six plastid sequences (matK, rbcL, atpB-rbcL, trnL-F, psbA-trnH, and rpl32-trnL) and 1,748 characters corresponding to two nuclear sequences (ITS and nepGS). Using different partitioning strategies and approaches (i.e., Bayesian inference, maximum likelihood, and maximum parsimony) for phylogeny reconstruction, different topologies and clade supports were determined. A total of 18 Ilex species was divided into two major groups (group I and II) in both plastid and nuclear phylogenies with some incongruences. Potential hybridization events may account, in part, for those phylogenetic uncertainties. The analyses, together with previously identified sequences, indicated that all 18 species were recovered within Eurasia or Asia/North America groups based on plastid data. Meanwhile, the species in group II in the nuclear phylogeny were placed in the Aquifolium clade, as inferred from traditional classification, whereas the species in group I belonged to several other clades. The divergence time of most of the 18 Ilex species was estimated to be not more than 10 million years ago. Based on the results of this study, we concluded that paleogeographical events and past climate changes during the same period might have played important roles in these diversifications. (author)
Reconstruction of mitogenomes by NGS and phylogenetic implications for leaf beetles.
Song, Nan; Yin, Xinming; Zhao, Xincheng; Chen, Junhua; Yin, Jian
2017-11-30
Mitochondrial genome (mitogenome) sequences are frequently used to infer phylogenetic relationships of insects at different taxonomic levels. Next-generation sequencing (NGS) techniques are revolutionizing many fields of biology, and allow for acquisition of insect mitogenomes for large number of species simultaneously. In this study, 20 full or partial mitogenomes were sequenced from pooled genomic DNA samples by NGS for leaf beetles (Chrysomelidae). Combined with published mitogenome sequences, a higher level phylogeny of Chrysomelidae was reconstructed under maximum likelihood and Bayesian inference with different models and various data treatments. The results revealed support for a basal position of Bruchinae within Chrysomelidae. In addition, two major subfamily groupings were recovered: one including seven subfamilies, namely Donaciinae, Criocerinae, Spilopyrinae, Cassidinae, Cryptocephalinae, Chlamisinae and Eumolpinae, another containing a non-monophyletic Chrysomelinae and a monophyletic Galerucinae.
Herbarium collection-based phylogenetics of the ragweeds (Ambrosia, Asteraceae).
Martin, Michael D; Quiroz-Claros, Elva; Brush, Grace S; Zimmer, Elizabeth A
2018-03-01
Ambrosia (Asteraceae) is a taxonomically difficult genus of weedy, wind-pollinated plants with an apparent center of diversity in the Sonoran Desert of North America. Determining Ambrosia's evolutionary relationships has been the subject of much interest, with numerous studies using morphological characters, cytology, comparative phytochemistry, and chloroplast restriction site variation to produce conflicting accounts the relationships between Ambrosia species, as well as the classification of their close relatives in Franseria and Hymenoclea. To resolve undetermined intra-generic relationships within Ambrosia, we used DNA extracted from tissues obtained from seed banks and herbarium collections to generate multi-locus genetic data representing nearly all putative species, including four from South America. We performed Bayesian and Maximum-Likelihood phylogenetic analyses of six chloroplast-genome and two nuclear-genome markers, enabling us to infer monophyly for the genus, resolve major infra-generic species clusters, as well as to resolve open questions about the evolutionary relationships of several Ambrosia species and former members of Franseria. We also provide molecular data supporting the hypothesis that A. sandersonii formed through the hybridization of A. eriocentra and A. salsola. The topology of our chloroplast DNA phylogeny is almost entirely congruent with the most recent molecular work based on chloroplast restriction site variation of a much more limited sampling of 14 North American species of Ambrosia, although our improved sampling of global Ambrosia diversity enables us to draw additional conclusions. As our study is the first direct DNA sequence-based phylogenetic analyses of Ambrosia, we analyze the data in relation to previous taxonomic studies and discuss several instances of chloroplast/nuclear incongruence that leave the precise geographic center of origin of Ambrosia in question. Copyright © 2017 Elsevier Inc. All rights reserved.
A phylogenetic perspective on the evolution of Mediterranean teleost fishes.
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Christine N Meynard
Full Text Available The Mediterranean Sea is a highly diverse, highly studied, and highly impacted biogeographic region, yet no phylogenetic reconstruction of fish diversity in this area has been published to date. Here, we infer the timing and geographic origins of Mediterranean teleost species diversity using nucleotide sequences collected from GenBank. We assembled a DNA supermatrix composed of four mitochondrial genes (12S ribosomal DNA, 16S ribosomal DNA, cytochrome c oxidase subunit I and cytochrome b and two nuclear genes (rhodopsin and recombination activating gene I, including 62% of Mediterranean teleost species plus 9 outgroups. Maximum likelihood and Bayesian phylogenetic and dating analyses were calibrated using 20 fossil constraints. An additional 124 species were grafted onto the chronogram according to their taxonomic affinity, checking for the effects of taxonomic coverage in subsequent diversification analyses. We then interpreted the time-line of teleost diversification in light of Mediterranean historical biogeography, distinguishing non-endemic natives, endemics and exotic species. Results show that the major Mediterranean orders are of Cretaceous origin, specifically ~100-80 Mya, and most Perciformes families originated 80-50 Mya. Two important clade origin events were detected. The first at 100-80 Mya, affected native and exotic species, and reflects a global diversification period at a time when the Mediterranean Sea did not yet exist. The second occurred during the last 50 Mya, and is noticeable among endemic and native species, but not among exotic species. This period corresponds to isolation of the Mediterranean from Indo-Pacific waters before the Messinian salinity crisis. The Mediterranean fish fauna illustrates well the assembly of regional faunas through origination and immigration, where dispersal and isolation have shaped the emergence of a biodiversity hotspot.
Forensic application of phylogenetic analyses - Exploration of suspected HIV-1 transmission case.
Siljic, Marina; Salemovic, Dubravka; Cirkovic, Valentina; Pesic-Pavlovic, Ivana; Ranin, Jovan; Todorovic, Marija; Nikolic, Slobodan; Jevtovic, Djordje; Stanojevic, Maja
2017-03-01
Transmission of human immunodeficiency virus (HIV) between individuals may have important legal implications and therefore may come to require forensic investigation based upon phylogenetic analysis. In criminal trials results of phylogenetic analyses have been used as evidence of responsibility for HIV transmission. In Serbia, as in many countries worldwide, exposure and deliberate transmission of HIV are criminalized. We present the results of applying state of the art phylogenetic analyses, based on pol and env genetic sequences, in exploration of suspected HIV transmission among three subjects: a man and two women, with presumed assumption of transmission direction from one woman to a man. Phylogenetic methods included relevant neighbor-joining (NJ), maximum likelihood (ML) and Bayesian methods of phylogenetic trees reconstruction and hypothesis testing, that has been shown to be the most sensitive for the reconstruction of epidemiological links mostly from sexually infected individuals. End-point limiting-dilution PCR (EPLD-PCR) assay, generating the minimum of 10 sequences per genetic region per subject, was performed to assess HIV quasispecies distribution and to explore the direction of HIV transmission between three subjects. Phylogenetic analysis revealed that the viral sequences from the three subjects were more genetically related to each other than to other strains circulating in the same area with the similar epidemiological profile, forming strongly supported transmission chain, which could be in favour of a priori hypothesis of one of the women infecting the man. However, in the EPLD based phylogenetic trees for both pol and env genetic region, viral sequences of one subject (man) were paraphyletic to those of two other subjects (women), implying the direction of transmission opposite to the a priori assumption. The dated tree in our analysis confirmed the clustering pattern of query sequences. Still, in the context of unsampled sequences and
Staggemeier, Vanessa Graziele; Diniz-Filho, José Alexandre Felizola; Forest, Félix; Lucas, Eve
2015-04-01
Myrcia section Aulomyrcia includes ∼120 species that are endemic to the Neotropics and disjunctly distributed in the moist Amazon and Atlantic coastal forests of Brazil. This paper presents the first comprehensive phylogenetic study of this group and this phylogeny is used as a basis to evaluate recent classification systems and to test alternative hypotheses associated with the history of this clade. Fifty-three taxa were sampled out of the 120 species currently recognized, plus 40 outgroup taxa, for one nuclear marker (ribosomal internal transcribed spacer) and four plastid markers (psbA-trnH, trnL-trnF, trnQ-rpS16 and ndhF). The relationships were reconstructed based on Bayesian and maximum likelihood analyses. Additionally, a likelihood approach, 'geographic state speciation and extinction', was used to estimate region- dependent rates of speciation, extinction and dispersal, comparing historically climatic stable areas (refugia) and unstable areas. Maximum likelihood and Bayesian inferences indicate that Myrcia and Marlierea are polyphyletic, and the internal groupings recovered are characterized by combinations of morphological characters. Phylogenetic relationships support a link between Amazonian and north-eastern species and between north-eastern and south-eastern species. Lower extinction rates within glacial refugia suggest that these areas were important in maintaining diversity in the Atlantic forest biodiversity hotspot. This study provides a robust phylogenetic framework to address important ecological questions for Myrcia s.l. within an evolutionary context, and supports the need to unite taxonomically the two traditional genera Myrcia and Marlierea in an expanded Myrcia s.l. Furthermore, this study offers valuable insights into the diversification of plant species in the highly impacted Atlantic forest of South America; evidence is presented that the lowest extinction rates are found inside refugia and that range expansion from unstable areas
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Patrick Kück
Full Text Available Martialinae are pale, eyeless and probably hypogaeic predatory ants. Morphological character sets suggest a close relationship to the ant subfamily Leptanillinae. Recent analyses based on molecular sequence data suggest that Martialinae are the sister group to all extant ants. However, by comparing molecular studies and different reconstruction methods, the position of Martialinae remains ambiguous. While this sister group relationship was well supported by Bayesian partitioned analyses, Maximum Likelihood approaches could not unequivocally resolve the position of Martialinae. By re-analysing a previous published molecular data set, we show that the Maximum Likelihood approach is highly appropriate to resolve deep ant relationships, especially between Leptanillinae, Martialinae and the remaining ant subfamilies. Based on improved alignments, alignment masking, and tree reconstructions with a sufficient number of bootstrap replicates, our results strongly reject a placement of Martialinae at the first split within the ant tree of life. Instead, we suggest that Leptanillinae are a sister group to all other extant ant subfamilies, whereas Martialinae branch off as a second lineage. This assumption is backed by approximately unbiased (AU tests, additional Bayesian analyses and split networks. Our results demonstrate clear effects of improved alignment approaches, alignment masking and data partitioning. We hope that our study illustrates the importance of thorough, comprehensible phylogenetic analyses using the example of ant relationships.
Yang, Ji; Gu, Hongya; Yang, Ziheng
2004-01-01
Chalcone synthase (CHS) is a key enzyme in the biosynthesis of flavonoides, which are important for the pigmentation of flowers and act as attractants to pollinators. Genes encoding CHS constitute a multigene family in which the copy number varies among plant species and functional divergence appears to have occurred repeatedly. In morning glories (Ipomoea), five functional CHS genes (A-E) have been described. Phylogenetic analysis of the Ipomoea CHS gene family revealed that CHS A, B, and C experienced accelerated rates of amino acid substitution relative to CHS D and E. To examine whether the CHS genes of the morning glories underwent adaptive evolution, maximum-likelihood models of codon substitution were used to analyze the functional sequences in the Ipomoea CHS gene family. These models used the nonsynonymous/synonymous rate ratio (omega = d(N)/ d(S)) as an indicator of selective pressure and allowed the ratio to vary among lineages or sites. Likelihood ratio test suggested significant variation in selection pressure among amino acid sites, with a small proportion of them detected to be under positive selection along the branches ancestral to CHS A, B, and C. Positive Darwinian selection appears to have promoted the divergence of subfamily ABC and subfamily DE and is at least partially responsible for a rate increase following gene duplication.
Profile-likelihood Confidence Intervals in Item Response Theory Models.
Chalmers, R Philip; Pek, Jolynn; Liu, Yang
2017-01-01
Confidence intervals (CIs) are fundamental inferential devices which quantify the sampling variability of parameter estimates. In item response theory, CIs have been primarily obtained from large-sample Wald-type approaches based on standard error estimates, derived from the observed or expected information matrix, after parameters have been estimated via maximum likelihood. An alternative approach to constructing CIs is to quantify sampling variability directly from the likelihood function with a technique known as profile-likelihood confidence intervals (PL CIs). In this article, we introduce PL CIs for item response theory models, compare PL CIs to classical large-sample Wald-type CIs, and demonstrate important distinctions among these CIs. CIs are then constructed for parameters directly estimated in the specified model and for transformed parameters which are often obtained post-estimation. Monte Carlo simulation results suggest that PL CIs perform consistently better than Wald-type CIs for both non-transformed and transformed parameters.
Mitogenomic phylogenetic analyses of the Delphinidae with an emphasis on the Globicephalinae
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de Stephanis Renaud
2011-03-01
Full Text Available Abstract Background Previous DNA-based phylogenetic studies of the Delphinidae family suggest it has undergone rapid diversification, as characterised by unresolved and poorly supported taxonomic relationships (polytomies for some of the species within this group. Using an increased amount of sequence data we test between alternative hypotheses of soft polytomies caused by rapid speciation, slow evolutionary rate and/or insufficient sequence data, and hard polytomies caused by simultaneous speciation within this family. Combining the mitogenome sequences of five new and 12 previously published species within the Delphinidae, we used Bayesian and maximum-likelihood methods to estimate the phylogeny from partitioned and unpartitioned mitogenome sequences. Further ad hoc tests were then conducted to estimate the support for alternative topologies. Results We found high support for all the relationships within our reconstructed phylogenies, and topologies were consistent between the Bayesian and maximum-likelihood trees inferred from partitioned and unpartitioned data. Resolved relationships included the placement of the killer whale (Orcinus orca as sister taxon to the rest of the Globicephalinae subfamily, placement of the Risso's dolphin (Grampus griseus within the Globicephalinae subfamily, removal of the white-beaked dolphin (Lagenorhynchus albirostris from the Delphininae subfamily and the placement of the rough-toothed dolphin (Steno bredanensis as sister taxon to the rest of the Delphininae subfamily rather than within the Globicephalinae subfamily. The additional testing of alternative topologies allowed us to reject all other putative relationships, with the exception that we were unable to reject the hypothesis that the relationship between L. albirostris and the Globicephalinae and Delphininae subfamilies was polytomic. Conclusion Despite their rapid diversification, the increased sequence data yielded by mitogenomes enables the
Generic maximum likely scale selection
DEFF Research Database (Denmark)
Pedersen, Kim Steenstrup; Loog, Marco; Markussen, Bo
2007-01-01
in this work is on applying this selection principle under a Brownian image model. This image model provides a simple scale invariant prior for natural images and we provide illustrative examples of the behavior of our scale estimation on such images. In these illustrative examples, estimation is based......The fundamental problem of local scale selection is addressed by means of a novel principle, which is based on maximum likelihood estimation. The principle is generally applicable to a broad variety of image models and descriptors, and provides a generic scale estimation methodology. The focus...
The prevalence of terraced treescapes in analyses of phylogenetic data sets.
Dobrin, Barbara H; Zwickl, Derrick J; Sanderson, Michael J
2018-04-04
The pattern of data availability in a phylogenetic data set may lead to the formation of terraces, collections of equally optimal trees. Terraces can arise in tree space if trees are scored with parsimony or with partitioned, edge-unlinked maximum likelihood. Theory predicts that terraces can be large, but their prevalence in contemporary data sets has never been surveyed. We selected 26 data sets and phylogenetic trees reported in recent literature and investigated the terraces to which the trees would belong, under a common set of inference assumptions. We examined terrace size as a function of the sampling properties of the data sets, including taxon coverage density (the proportion of taxon-by-gene positions with any data present) and a measure of gene sampling "sufficiency". We evaluated each data set in relation to the theoretical minimum gene sampling depth needed to reduce terrace size to a single tree, and explored the impact of the terraces found in replicate trees in bootstrap methods. Terraces were identified in nearly all data sets with taxon coverage densities tree. Terraces found during bootstrap resampling reduced overall support. If certain inference assumptions apply, trees estimated from empirical data sets often belong to large terraces of equally optimal trees. Terrace size correlates to data set sampling properties. Data sets seldom include enough genes to reduce terrace size to one tree. When bootstrap replicate trees lie on a terrace, statistical support for phylogenetic hypotheses may be reduced. Although some of the published analyses surveyed were conducted with edge-linked inference models (which do not induce terraces), unlinked models have been used and advocated. The present study describes the potential impact of that inference assumption on phylogenetic inference in the context of the kinds of multigene data sets now widely assembled for large-scale tree construction.
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Jianlong Li
Full Text Available Anemonefishes (Pomacentridae Amphiprioninae are a group of 30 valid coral reef fish species with their phylogenetic relationships still under debate. The eight available mitogenomes of anemonefishes were used to reconstruct the molecular phylogenetic tree; six were obtained from this study (Amphiprion clarkii, A. frenatus, A. percula, A. perideraion, A. polymnus and Premnas biaculeatus and two from GenBank (A. bicinctus and A. ocellaris. The seven Amphiprion species represent all four subgenera and P. biaculeatus is the only species from Premnas. The eight mitogenomes of anemonefishes encoded 13 protein-coding genes, two rRNA genes, 22 tRNA genes and two main non-coding regions, with the gene arrangement and translation direction basically identical to other typical vertebrate mitogenomes. Among the 13 protein-coding genes, A. ocellaris (AP006017 and A. percula (KJ174497 had the same length in ND5 with 1,866 bp, which were three nucleotides less than the other six anemonefishes. Both structures of ND5, however, could translate to amino acid successfully. Only four mitogenomes had the tandem repeats in D-loop; the tandem repeats were located in downstream after Conserved Sequence Block rather than the upstream and repeated in a simply way. The phylogenetic utility was tested with Bayesian and Maximum Likelihood methods using all 13 protein-coding genes. The results strongly supported that the subfamily Amphiprioninae was monophyletic and P. biaculeatus should be assigned to the genus Amphiprion. Premnas biaculeatus with the percula complex were revealed to be the ancient anemonefish species. The tree forms of ND1, COIII, ND4, Cytb, Cytb+12S rRNA, Cytb+COI and Cytb+COI+12S rRNA were similar to that 13 protein-coding genes, therefore, we suggested that the suitable single mitochondrial gene for phylogenetic analysis of anemonefishes maybe Cytb. Additional mitogenomes of anemonefishes with a combination of nuclear markers will be useful to
Zhang, Dong; Yan, Liping; Zhang, Ming; Chu, Hongjun; Cao, Jie; Li, Kai; Hu, Defu; Pape, Thomas
2016-01-01
The complete mitogenome of the horse stomach bot fly Gasterophilus pecorum (Fabricius) and a near-complete mitogenome of Wohlfahrt's wound myiasis fly Wohlfahrtia magnifica (Schiner) were sequenced. The mitogenomes contain the typical 37 mitogenes found in metazoans, organized in the same order and orientation as in other cyclorrhaphan Diptera. Phylogenetic analyses of mitogenomes from 38 calyptrate taxa with and without two non-calyptrate outgroups were performed using Bayesian Inference and Maximum Likelihood. Three sub-analyses were performed on the concatenated data: (1) not partitioned; (2) partitioned by gene; (3) 3rd codon positions of protein-coding genes omitted. We estimated the contribution of each of the mitochondrial genes for phylogenetic analysis, as well as the effect of some popular methodologies on calyptrate phylogeny reconstruction. In the favoured trees, the Oestroidea are nested within the muscoid grade. Relationships at the family level within Oestroidea are (remaining Calliphoridae (Sarcophagidae (Oestridae, Pollenia + Tachinidae))). Our mito-phylogenetic reconstruction of the Calyptratae presents the most extensive taxon coverage so far, and the risk of long-branch attraction is reduced by an appropriate selection of outgroups. We find that in the Calyptratae the ND2, ND5, ND1, COIII, and COI genes are more phylogenetically informative compared with other mitochondrial protein-coding genes. Our study provides evidence that data partitioning and the inclusion of conserved tRNA genes have little influence on calyptrate phylogeny reconstruction, and that the 3rd codon positions of protein-coding genes are not saturated and therefore should be included. PMID:27019632
Phylogenetic escalation and decline of plant defense strategies
Agrawal, Anurag A.; Fishbein, Mark
2008-01-01
As the basal resource in most food webs, plants have evolved myriad strategies to battle consumption by herbivores. Over the past 50 years, plant defense theories have been formulated to explain the remarkable variation in abundance, distribution, and diversity of secondary chemistry and other defensive traits. For example, classic theories of enemy-driven evolutionary dynamics have hypothesized that defensive traits escalate through the diversification process. Despite the fact that macroevolutionary patterns are an explicit part of defense theories, phylogenetic analyses have not been previously attempted to disentangle specific predictions concerning (i) investment in resistance traits, (ii) recovery after damage, and (iii) plant growth rate. We constructed a molecular phylogeny of 38 species of milkweed and tested four major predictions of defense theory using maximum-likelihood methods. We did not find support for the growth-rate hypothesis. Our key finding was a pattern of phyletic decline in the three most potent resistance traits (cardenolides, latex, and trichomes) and an escalation of regrowth ability. Our neontological approach complements more common paleontological approaches to discover directional trends in the evolution of life and points to the importance of natural enemies in the macroevolution of species. The finding of macroevolutionary escalating regowth ability and declining resistance provides a window into the ongoing coevolutionary dynamics between plants and herbivores and suggests a revision of classic plant defense theory. Where plants are primarily consumed by specialist herbivores, regrowth (or tolerance) may be favored over resistance traits during the diversification process. PMID:18645183
Fast optimization of statistical potentials for structurally constrained phylogenetic models
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Rodrigue Nicolas
2009-09-01
Full Text Available Abstract Background Statistical approaches for protein design are relevant in the field of molecular evolutionary studies. In recent years, new, so-called structurally constrained (SC models of protein-coding sequence evolution have been proposed, which use statistical potentials to assess sequence-structure compatibility. In a previous work, we defined a statistical framework for optimizing knowledge-based potentials especially suited to SC models. Our method used the maximum likelihood principle and provided what we call the joint potentials. However, the method required numerical estimations by the use of computationally heavy Markov Chain Monte Carlo sampling algorithms. Results Here, we develop an alternative optimization procedure, based on a leave-one-out argument coupled to fast gradient descent algorithms. We assess that the leave-one-out potential yields very similar results to the joint approach developed previously, both in terms of the resulting potential parameters, and by Bayes factor evaluation in a phylogenetic context. On the other hand, the leave-one-out approach results in a considerable computational benefit (up to a 1,000 fold decrease in computational time for the optimization procedure. Conclusion Due to its computational speed, the optimization method we propose offers an attractive alternative for the design and empirical evaluation of alternative forms of potentials, using large data sets and high-dimensional parameterizations.
Pendeteksian Outlier pada Regresi Nonlinier dengan Metode statistik Likelihood Displacement
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Siti Tabi'atul Hasanah
2012-11-01
Full Text Available Outlier is an observation that much different (extreme from the other observational data, or data can be interpreted that do not follow the general pattern of the model. Sometimes outliers provide information that can not be provided by other data. That's why outliers should not just be eliminated. Outliers can also be an influential observation. There are many methods that can be used to detect of outliers. In previous studies done on outlier detection of linear regression. Next will be developed detection of outliers in nonlinear regression. Nonlinear regression here is devoted to multiplicative nonlinear regression. To detect is use of statistical method likelihood displacement. Statistical methods abbreviated likelihood displacement (LD is a method to detect outliers by removing the suspected outlier data. To estimate the parameters are used to the maximum likelihood method, so we get the estimate of the maximum. By using LD method is obtained i.e likelihood displacement is thought to contain outliers. Further accuracy of LD method in detecting the outliers are shown by comparing the MSE of LD with the MSE from the regression in general. Statistic test used is Λ. Initial hypothesis was rejected when proved so is an outlier.
Constraint likelihood analysis for a network of gravitational wave detectors
International Nuclear Information System (INIS)
Klimenko, S.; Rakhmanov, M.; Mitselmakher, G.; Mohanty, S.
2005-01-01
We propose a coherent method for detection and reconstruction of gravitational wave signals with a network of interferometric detectors. The method is derived by using the likelihood ratio functional for unknown signal waveforms. In the likelihood analysis, the global maximum of the likelihood ratio over the space of waveforms is used as the detection statistic. We identify a problem with this approach. In the case of an aligned pair of detectors, the detection statistic depends on the cross correlation between the detectors as expected, but this dependence disappears even for infinitesimally small misalignments. We solve the problem by applying constraints on the likelihood functional and obtain a new class of statistics. The resulting method can be applied to data from a network consisting of any number of detectors with arbitrary detector orientations. The method allows us reconstruction of the source coordinates and the waveforms of two polarization components of a gravitational wave. We study the performance of the method with numerical simulations and find the reconstruction of the source coordinates to be more accurate than in the standard likelihood method
A biclustering algorithm for binary matrices based on penalized Bernoulli likelihood
Lee, Seokho; Huang, Jianhua Z.
2013-01-01
We propose a new biclustering method for binary data matrices using the maximum penalized Bernoulli likelihood estimation. Our method applies a multi-layer model defined on the logits of the success probabilities, where each layer represents a
Exploring the relationship between sequence similarity and accurate phylogenetic trees.
Cantarel, Brandi L; Morrison, Hilary G; Pearson, William
2006-11-01
We have characterized the relationship between accurate phylogenetic reconstruction and sequence similarity, testing whether high levels of sequence similarity can consistently produce accurate evolutionary trees. We generated protein families with known phylogenies using a modified version of the PAML/EVOLVER program that produces insertions and deletions as well as substitutions. Protein families were evolved over a range of 100-400 point accepted mutations; at these distances 63% of the families shared significant sequence similarity. Protein families were evolved using balanced and unbalanced trees, with ancient or recent radiations. In families sharing statistically significant similarity, about 60% of multiple sequence alignments were 95% identical to true alignments. To compare recovered topologies with true topologies, we used a score that reflects the fraction of clades that were correctly clustered. As expected, the accuracy of the phylogenies was greatest in the least divergent families. About 88% of phylogenies clustered over 80% of clades in families that shared significant sequence similarity, using Bayesian, parsimony, distance, and maximum likelihood methods. However, for protein families with short ancient branches (ancient radiation), only 30% of the most divergent (but statistically significant) families produced accurate phylogenies, and only about 70% of the second most highly conserved families, with median expectation values better than 10(-60), produced accurate trees. These values represent upper bounds on expected tree accuracy for sequences with a simple divergence history; proteins from 700 Giardia families, with a similar range of sequence similarities but considerably more gaps, produced much less accurate trees. For our simulated insertions and deletions, correct multiple sequence alignments did not perform much better than those produced by T-COFFEE, and including sequences with expressed sequence tag-like sequencing errors did not
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John A. Lees
2018-03-01
Full Text Available Background: Phylogenetic reconstruction is a necessary first step in many analyses which use whole genome sequence data from bacterial populations. There are many available methods to infer phylogenies, and these have various advantages and disadvantages, but few unbiased comparisons of the range of approaches have been made. Methods: We simulated data from a defined “true tree” using a realistic evolutionary model. We built phylogenies from this data using a range of methods, and compared reconstructed trees to the true tree using two measures, noting the computational time needed for different phylogenetic reconstructions. We also used real data from Streptococcus pneumoniae alignments to compare individual core gene trees to a core genome tree. Results: We found that, as expected, maximum likelihood trees from good quality alignments were the most accurate, but also the most computationally intensive. Using less accurate phylogenetic reconstruction methods, we were able to obtain results of comparable accuracy; we found that approximate results can rapidly be obtained using genetic distance based methods. In real data we found that highly conserved core genes, such as those involved in translation, gave an inaccurate tree topology, whereas genes involved in recombination events gave inaccurate branch lengths. We also show a tree-of-trees, relating the results of different phylogenetic reconstructions to each other. Conclusions: We recommend three approaches, depending on requirements for accuracy and computational time. Quicker approaches that do not perform full maximum likelihood optimisation may be useful for many analyses requiring a phylogeny, as generating a high quality input alignment is likely to be the major limiting factor of accurate tree topology. We have publicly released our simulated data and code to enable further comparisons.
Phylogenetic diversity and biodiversity indices on phylogenetic networks.
Wicke, Kristina; Fischer, Mareike
2018-04-01
In biodiversity conservation it is often necessary to prioritize the species to conserve. Existing approaches to prioritization, e.g. the Fair Proportion Index and the Shapley Value, are based on phylogenetic trees and rank species according to their contribution to overall phylogenetic diversity. However, in many cases evolution is not treelike and thus, phylogenetic networks have been developed as a generalization of phylogenetic trees, allowing for the representation of non-treelike evolutionary events, such as hybridization. Here, we extend the concepts of phylogenetic diversity and phylogenetic diversity indices from phylogenetic trees to phylogenetic networks. On the one hand, we consider the treelike content of a phylogenetic network, e.g. the (multi)set of phylogenetic trees displayed by a network and the so-called lowest stable ancestor tree associated with it. On the other hand, we derive the phylogenetic diversity of subsets of taxa and biodiversity indices directly from the internal structure of the network. We consider both approaches that are independent of so-called inheritance probabilities as well as approaches that explicitly incorporate these probabilities. Furthermore, we introduce our software package NetDiversity, which is implemented in Perl and allows for the calculation of all generalized measures of phylogenetic diversity and generalized phylogenetic diversity indices established in this note that are independent of inheritance probabilities. We apply our methods to a phylogenetic network representing the evolutionary relationships among swordtails and platyfishes (Xiphophorus: Poeciliidae), a group of species characterized by widespread hybridization. Copyright © 2018 Elsevier Inc. All rights reserved.
Ancestral sequence reconstruction with Maximum Parsimony
Herbst, Lina; Fischer, Mareike
2017-01-01
One of the main aims in phylogenetics is the estimation of ancestral sequences based on present-day data like, for instance, DNA alignments. One way to estimate the data of the last common ancestor of a given set of species is to first reconstruct a phylogenetic tree with some tree inference method and then to use some method of ancestral state inference based on that tree. One of the best-known methods both for tree inference as well as for ancestral sequence inference is Maximum Parsimony (...
Licona-Vera, Yuyini; Ornelas, Juan Francisco
2017-06-05
Geographical and temporal patterns of diversification in bee hummingbirds (Mellisugini) were assessed with respect to the evolution of migration, critical for colonization of North America. We generated a dated multilocus phylogeny of the Mellisugini based on a dense sampling using Bayesian inference, maximum-likelihood and maximum parsimony methods, and reconstructed the ancestral states of distributional areas in a Bayesian framework and migratory behavior using maximum parsimony, maximum-likelihood and re-rooting methods. All phylogenetic analyses confirmed monophyly of the Mellisugini and the inclusion of Atthis, Calothorax, Doricha, Eulidia, Mellisuga, Microstilbon, Myrmia, Tilmatura, and Thaumastura. Mellisugini consists of two clades: (1) South American species (including Tilmatura dupontii), and (2) species distributed in North and Central America and the Caribbean islands. The second clade consists of four subclades: Mexican (Calothorax, Doricha) and Caribbean (Archilochus, Calliphlox, Mellisuga) sheartails, Calypte, and Selasphorus (incl. Atthis). Coalescent-based dating places the origin of the Mellisugini in the mid-to-late Miocene, with crown ages of most subclades in the early Pliocene, and subsequent species splits in the Pleistocene. Bee hummingbirds reached western North America by the end of the Miocene and the ancestral mellisuginid (bee hummingbirds) was reconstructed as sedentary, with four independent gains of migratory behavior during the evolution of the Mellisugini. Early colonization of North America and subsequent evolution of migration best explained biogeographic and diversification patterns within the Mellisugini. The repeated evolution of long-distance migration by different lineages was critical for the colonization of North America, contributing to the radiation of bee hummingbirds. Comparative phylogeography is needed to test whether the repeated evolution of migration resulted from northward expansion of southern sedentary
Fenn, J Daniel; Song, Hojun; Cameron, Stephen L; Whiting, Michael F
2008-10-01
The phylogenetic utility of mitochondrial genomes (mtgenomes) is examined using the framework of a preliminary phylogeny of Orthoptera. This study presents five newly sequenced genomes from four orthopteran families. While all ensiferan and polyneopteran taxa retain the ancestral gene order, all caeliferan lineages including the newly sequenced caeliferan species contain a tRNA rearrangement from the insect ground plan tRNA(Lys)(K)-tRNA(Asp)(D) swapping to tRNA(Asp) (D)-tRNA(Lys) (K) confirming that this rearrangement is a possible molecular synapomorphy for this suborder. The phylogenetic signal in mtgenomes is rigorously examined under the analytical regimens of parsimony, maximum likelihood and Bayesian inference, along with how gene inclusion/exclusion, data recoding, gap coding, and different partitioning schemes influence the phylogenetic reconstruction. When all available data are analyzed simultaneously, the monophyly of Orthoptera and its two suborders, Caelifera and Ensifera, are consistently recovered in the context of our taxon sampling, regardless of the optimality criteria. When protein-coding genes are analyzed as a single partition, nearly identical topology to the combined analyses is recovered, suggesting that much of the signals of the mtgenome come from the protein-coding genes. Transfer and ribosomal RNAs perform poorly when analyzed individually, but contribute signal when analyzed in combination with the protein-coding genes. Inclusion of third codon position of the protein-coding genes does not negatively affect the phylogenetic reconstruction when all genes are analyzed together, whereas recoding of the protein-coding genes into amino acid sequences introduces artificial resolution. Over-partitioning in a Bayesian framework appears to have a negative effect in achieving convergence. Our findings suggest that the best phylogenetic inferences are made when all available nucleotide data from the mtgenome are analyzed simultaneously, and that
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Tiago R Simões
Full Text Available Mosasauroids were a successful lineage of squamate reptiles (lizards and snakes that radiated during the Late Cretaceous (95-66 million years ago. They can be considered one of the few lineages in the evolutionary history of tetrapods to have acquired a fully aquatic lifestyle, similarly to whales, ichthyosaurs and plesiosaurs. Despite a long history of research on this group, their phylogenetic relationships have only been tested so far using traditional (unweighted maximum parsimony. However, hypotheses of mosasauroid relationships and the recently proposed multiple origins of aquatically adapted pelvic and pedal features in this group can be more thoroughly tested by methods that take into account variation in branch lengths and evolutionary rates. In this study, we present the first mosasauroid phylogenetic analysis performed under different analytical methods, including maximum likelihood, Bayesian inference, and implied weighting maximum parsimony. The results indicate a lack of congruence in the topological position of halisaurines and Dallasaurus. Additionally, the genus Prognathodon is paraphyletic under all hypotheses. Interestingly, a number of traditional mosasauroid clades become weakly supported, or unresolved, under Bayesian analyses. The reduced resolutions in some consensus trees create ambiguities concerning the evolution of fully aquatic pelvic/pedal conditions under many analyses. However, when enough resolution was obtained, reversals of the pelvic/pedal conditions were favoured by parsimony and likelihood ancestral state reconstructions instead of independent origins of aquatic features in mosasauroids. It is concluded that most of the observed discrepancies among the results can be associated with different analytical procedures, but also due to limited postcranial data on halisaurines, yaguarasaurines and Dallasaurus.
Vernygora, Oksana; Paparella, Ilaria; Jimenez-Huidobro, Paulina; Caldwell, Michael W.
2017-01-01
Mosasauroids were a successful lineage of squamate reptiles (lizards and snakes) that radiated during the Late Cretaceous (95–66 million years ago). They can be considered one of the few lineages in the evolutionary history of tetrapods to have acquired a fully aquatic lifestyle, similarly to whales, ichthyosaurs and plesiosaurs. Despite a long history of research on this group, their phylogenetic relationships have only been tested so far using traditional (unweighted) maximum parsimony. However, hypotheses of mosasauroid relationships and the recently proposed multiple origins of aquatically adapted pelvic and pedal features in this group can be more thoroughly tested by methods that take into account variation in branch lengths and evolutionary rates. In this study, we present the first mosasauroid phylogenetic analysis performed under different analytical methods, including maximum likelihood, Bayesian inference, and implied weighting maximum parsimony. The results indicate a lack of congruence in the topological position of halisaurines and Dallasaurus. Additionally, the genus Prognathodon is paraphyletic under all hypotheses. Interestingly, a number of traditional mosasauroid clades become weakly supported, or unresolved, under Bayesian analyses. The reduced resolutions in some consensus trees create ambiguities concerning the evolution of fully aquatic pelvic/pedal conditions under many analyses. However, when enough resolution was obtained, reversals of the pelvic/pedal conditions were favoured by parsimony and likelihood ancestral state reconstructions instead of independent origins of aquatic features in mosasauroids. It is concluded that most of the observed discrepancies among the results can be associated with different analytical procedures, but also due to limited postcranial data on halisaurines, yaguarasaurines and Dallasaurus. PMID:28467456
The Laplace Likelihood Ratio Test for Heteroscedasticity
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J. Martin van Zyl
2011-01-01
Full Text Available It is shown that the likelihood ratio test for heteroscedasticity, assuming the Laplace distribution, gives good results for Gaussian and fat-tailed data. The likelihood ratio test, assuming normality, is very sensitive to any deviation from normality, especially when the observations are from a distribution with fat tails. Such a likelihood test can also be used as a robust test for a constant variance in residuals or a time series if the data is partitioned into groups.
Li, Xiao-xu; Liu, Cheng; Li, Wei; Zhang, Zeng-lin; Gao, Xiao-ming; Zhou, Hui; Guo, Yong-feng
2016-05-01
Members of the plant-specific WOX transcription factor family have been reported to play important roles in cell to cell communication as well as other physiological and developmental processes. In this study, ten members of the WOX transcription factor family were identified in Solanum lycopersicum with HMMER. Neighbor-joining phylogenetic tree, maximum-likelihood tree and Bayesian-inference tree were constructed and similar topologies were shown using the protein sequences of the homeodomain. Phylogenetic study revealed that the 25 WOX family members from Arabidopsis and tomato fall into three clades and nine subfamilies. The patterns of exon-intron structures and organization of conserved domains in Arabidopsis and tomato were consistent based on the phylogenetic results. Transcriptome analysis showed that the expression patterns of SlWOXs were different in different tissue types. Gene Ontology (GO) analysis suggested that, as transcription factors, the SlWOX family members could be involved in a number of biological processes including cell to cell communication and tissue development. Our results are useful for future studies on WOX family members in tomato and other plant species.
Agaricus section Xanthodermatei: a phylogenetic reconstruction with commentary on taxa.
Kerrigan, Richard W; Callac, Philippe; Guinberteau, Jacques; Challen, Michael P; Parra, Luis A
2005-01-01
Agaricus section Xanthodermatei comprises a group of species allied to A. xanthodermus and generally characterized by basidiomata having phenolic odors, transiently yellowing discolorations in some parts of the basidiome, Schaeffer's reaction negative, and mild to substantial toxicity. The section has a global distribution, while most included species have distributions restricted to regions of single continents. Using specimens and cultures from Europe, North America, and Hawaii, we analyzed DNA sequences from the ITS1+2 region of the nuclear rDNA to identify and characterize phylogenetically distinct entities and to construct a hypothesis of relationships, both among members of the section and with representative taxa from other sections of the genus. 61 sequences from affiliated taxa, plus 20 from six (or seven) other sections of Agaricus, and one Micropsalliota sequence, were evaluated under distance, maximum parsimony and maximum likelihood methods. We recognized 21 discrete entities in Xanthodermatei, including 14 established species and 7 new ones, three of which are described elsewhere. Four species from California, New Mexico, and France deserve further study before they are described. Type studies of American taxa are particularly emphasized, and a lectotype is designated for A. californicus. Section Xanthodermatei formed a single clade in most analyses, indicating that the traditional sectional characters noted above are good unifying characters that appear to have arisen only once within Agaricus. Deep divisions within the sequence-derived structure of the section could be interpreted as subsections in Xanthodermatei; however, various considerations led us to refrain from proposing new supraspecific taxa. The nearest neighbors of section Xanthodermatei are putatively in section Duploannulati.
A Universal Phylogenetic Tree.
Offner, Susan
2001-01-01
Presents a universal phylogenetic tree suitable for use in high school and college-level biology classrooms. Illustrates the antiquity of life and that all life is related, even if it dates back 3.5 billion years. Reflects important evolutionary relationships and provides an exciting way to learn about the history of life. (SAH)
Liu, Kevin; Warnow, Tandy J; Holder, Mark T; Nelesen, Serita M; Yu, Jiaye; Stamatakis, Alexandros P; Linder, C Randal
2012-01-01
Highly accurate estimation of phylogenetic trees for large data sets is difficult, in part because multiple sequence alignments must be accurate for phylogeny estimation methods to be accurate. Coestimation of alignments and trees has been attempted but currently only SATé estimates reasonably accurate trees and alignments for large data sets in practical time frames (Liu K., Raghavan S., Nelesen S., Linder C.R., Warnow T. 2009b. Rapid and accurate large-scale coestimation of sequence alignments and phylogenetic trees. Science. 324:1561-1564). Here, we present a modification to the original SATé algorithm that improves upon SATé (which we now call SATé-I) in terms of speed and of phylogenetic and alignment accuracy. SATé-II uses a different divide-and-conquer strategy than SATé-I and so produces smaller more closely related subsets than SATé-I; as a result, SATé-II produces more accurate alignments and trees, can analyze larger data sets, and runs more efficiently than SATé-I. Generally, SATé is a metamethod that takes an existing multiple sequence alignment method as an input parameter and boosts the quality of that alignment method. SATé-II-boosted alignment methods are significantly more accurate than their unboosted versions, and trees based upon these improved alignments are more accurate than trees based upon the original alignments. Because SATé-I used maximum likelihood (ML) methods that treat gaps as missing data to estimate trees and because we found a correlation between the quality of tree/alignment pairs and ML scores, we explored the degree to which SATé's performance depends on using ML with gaps treated as missing data to determine the best tree/alignment pair. We present two lines of evidence that using ML with gaps treated as missing data to optimize the alignment and tree produces very poor results. First, we show that the optimization problem where a set of unaligned DNA sequences is given and the output is the tree and alignment of
Coalescent methods for estimating phylogenetic trees.
Liu, Liang; Yu, Lili; Kubatko, Laura; Pearl, Dennis K; Edwards, Scott V
2009-10-01
We review recent models to estimate phylogenetic trees under the multispecies coalescent. Although the distinction between gene trees and species trees has come to the fore of phylogenetics, only recently have methods been developed that explicitly estimate species trees. Of the several factors that can cause gene tree heterogeneity and discordance with the species tree, deep coalescence due to random genetic drift in branches of the species tree has been modeled most thoroughly. Bayesian approaches to estimating species trees utilizes two likelihood functions, one of which has been widely used in traditional phylogenetics and involves the model of nucleotide substitution, and the second of which is less familiar to phylogeneticists and involves the probability distribution of gene trees given a species tree. Other recent parametric and nonparametric methods for estimating species trees involve parsimony criteria, summary statistics, supertree and consensus methods. Species tree approaches are an appropriate goal for systematics, appear to work well in some cases where concatenation can be misleading, and suggest that sampling many independent loci will be paramount. Such methods can also be challenging to implement because of the complexity of the models and computational time. In addition, further elaboration of the simplest of coalescent models will be required to incorporate commonly known issues such as deviation from the molecular clock, gene flow and other genetic forces.
Heterotachy and long-branch attraction in phylogenetics
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Rodrigue Nicolas
2005-10-01
Full Text Available Abstract Background Probabilistic methods have progressively supplanted the Maximum Parsimony (MP method for inferring phylogenetic trees. One of the major reasons for this shift was that MP is much more sensitive to the Long Branch Attraction (LBA artefact than is Maximum Likelihood (ML. However, recent work by Kolaczkowski and Thornton suggested, on the basis of simulations, that MP is less sensitive than ML to tree reconstruction artefacts generated by heterotachy, a phenomenon that corresponds to shifts in site-specific evolutionary rates over time. These results led these authors to recommend that the results of ML and MP analyses should be both reported and interpreted with the same caution. This specific conclusion revived the debate on the choice of the most accurate phylogenetic method for analysing real data in which various types of heterogeneities occur. However, variation of evolutionary rates across species was not explicitly incorporated in the original study of Kolaczkowski and Thornton, and in most of the subsequent heterotachous simulations published to date, where all terminal branch lengths were kept equal, an assumption that is biologically unrealistic. Results In this report, we performed more realistic simulations to evaluate the relative performance of MP and ML methods when two kinds of heterogeneities are considered: (i within-site rate variation (heterotachy, and (ii rate variation across lineages. Using a similar protocol as Kolaczkowski and Thornton to generate heterotachous datasets, we found that heterotachy, which constitutes a serious violation of existing models, decreases the accuracy of ML whatever the level of rate variation across lineages. In contrast, the accuracy of MP can either increase or decrease when the level of heterotachy increases, depending on the relative branch lengths. This result demonstrates that MP is not insensitive to heterotachy, contrary to the report of Kolaczkowski and Thornton
Haklová, B; Majláthová, V; Majláth, I; Harris, D J; Petrilla, V; Litschka-Koen, T; Oros, M; Peťko, B
2014-03-01
The blood parasites from the genus Hepatozoon Miller, 1908 (Apicomplexa: Adeleida: Hepatozoidae) represent the most common intracellular protozoan parasites found in snakes. In the present study, we examined 209 individuals of snakes, from different zoogeographical regions (Africa, America, Asia and Europe), for the occurrence of blood parasites using both molecular and microscopic examination methods, and assess phylogenetic relationships of all Hepatozoon parasites from snakes for the first time. In total, 178 blood smears obtained from 209 individuals, representing 40 species, were examined, from which Hepatozoon unicellular parasites were found in 26 samples (14·6% prevalence). Out of 180 samples tested by molecular method polymerase chain reaction (PCR), the presence of parasites was observed in 21 individuals (prevalence 11·6%): 14 snakes from Africa belonging to six genera (Dendroaspis, Dispholidus, Mehelya, Naja, Philothamnus and Python), five snakes from Asia from the genus Morelia and two snakes from America, from two genera (Coluber and Corallus). The intensity of infection varied from one to 1433 infected cells per 10 000 erythrocytes. Results of phylogenetic analyses (Bayesian and Maximum Likelihood) revealed the existence of five haplotypes divided into four main lineages. The present data also indicate neither geographical pattern of studied Hepatozoon sp., nor congruency in the host association.
Damkliang, Kasikrit; Tandayya, Pichaya; Sangket, Unitsa; Pasomsub, Ekawat
2016-11-28
At the present, coding sequence (CDS) has been discovered and larger CDS is being revealed frequently. Approaches and related tools have also been developed and upgraded concurrently, especially for phylogenetic tree analysis. This paper proposes an integrated automatic Taverna workflow for the phylogenetic tree inferring analysis using public access web services at European Bioinformatics Institute (EMBL-EBI) and Swiss Institute of Bioinformatics (SIB), and our own deployed local web services. The workflow input is a set of CDS in the Fasta format. The workflow supports 1,000 to 20,000 numbers in bootstrapping replication. The workflow performs the tree inferring such as Parsimony (PARS), Distance Matrix - Neighbor Joining (DIST-NJ), and Maximum Likelihood (ML) algorithms of EMBOSS PHYLIPNEW package based on our proposed Multiple Sequence Alignment (MSA) similarity score. The local web services are implemented and deployed into two types using the Soaplab2 and Apache Axis2 deployment. There are SOAP and Java Web Service (JWS) providing WSDL endpoints to Taverna Workbench, a workflow manager. The workflow has been validated, the performance has been measured, and its results have been verified. Our workflow's execution time is less than ten minutes for inferring a tree with 10,000 replicates of the bootstrapping numbers. This paper proposes a new integrated automatic workflow which will be beneficial to the bioinformaticians with an intermediate level of knowledge and experiences. All local services have been deployed at our portal http://bioservices.sci.psu.ac.th.
Directory of Open Access Journals (Sweden)
Xin-Nan Jia
Full Text Available In this study, the authors first obtained the mitochondrial genome of Somanniathelphusa boyangensis. The results showed that the mitochondrial genome is 17,032bp in length, included 13 protein-coding genes, 2 rRNAs genes, 22 tRNAs genes and 1 putative control region, and it has the characteristics of the metazoan mitochondrial genome A+T bias. All tRNA genes display the typical clover-leaf secondary structure except tRNASer(AGN, which has lost the dihydroxyuridine arm. The GenBank database contains the mitochondrial genomes of representatives of approximately 22 families of Brachyura, comprising 56 species, including 4 species of freshwater crab. The authors established the phylogenetic relationships using the maximum likelihood and Bayesian inference methods. The phylogenetic relationship indicated that the molecular taxonomy of S. boyangensis is consistent with current morphological classification, and Parathelphusidae and Potamidae are derived within the freshwater clade or as part of it. In addition, the authors used the COX1 sequence of Somanniathelphusa in GenBank and the COX1 sequence of S. boyangensis to estimated the divergence time of this genus. The result displayed that the divergence time of Somanniathelphusa qiongshanensis is consistent with the separation of Hainan Island from mainland China in the Beibu Gulf, and the divergence time for Somanniathelphusa taiwanensis and Somanniathelphusa amoyensis is consistent with the separation of Taiwan Province from Mainland China at Fujian Province. These data indicate that geologic events influenced speciation of the genus Somanniathelphusa.
Molecular and phylogenetic evidence of chikungunya virus circulating in Assam, India
Directory of Open Access Journals (Sweden)
Prafulla Dutta
2017-01-01
Full Text Available Purpose: Northeast Region of India possesses an abundant number of Aedes mosquitoes, the common vector for Dengue and Chikungunya (CHIK. Dengue is reported every year from Assam, but active surveillance for CHIK virus (CHIKV infection is lacking in this part of India. Therefore, this present study has been undertaken to detect any CHIKV infection during a dengue outbreak in Assam. Materials and Methods: A total of 42 dengue negative samples collected from Guwahati were screened for the presence of CHIK IgM antibodies. Further, all the samples were processed for CHIKV RNA detection by reverse transcriptase-polymerase chain reaction (RT-PCR. Phylogenetic analysis was done by Maximum Likelihood method using Kimura-2 parameter model. Results: No IgM positivity was found in the processed samples; however, 7 samples were positive for CHIKV by RT-PCR. Phylogenetic analysis revealed that the circulating CHIKV belonged to Eastern, Central and Southern African genotype. Sequence analysis showed two uniform nucleotide substitutions and very less amino acid substitution. Conclusion: Silent existence of CHIKV beside dengue is reported from this study. Therefore, CHIKV diagnosis should be included as a regular practice for active surveillance of the disease and its accomplishment before commencing an outbreak.
Matsen, Frederick A
2010-06-01
This article introduces constNJ (constrained neighbor-joining), an algorithm for phylogenetic reconstruction of sets of trees with constrained pairwise rooted subtree-prune-regraft (rSPR) distance. We are motivated by the problem of constructing sets of trees that must fit into a recombination, hybridization, or similar network. Rather than first finding a set of trees that are optimal according to a phylogenetic criterion (e.g., likelihood or parsimony) and then attempting to fit them into a network, constNJ estimates the trees while enforcing specified rSPR distance constraints. The primary input for constNJ is a collection of distance matrices derived from sequence blocks which are assumed to have evolved in a tree-like manner, such as blocks of an alignment which do not contain any recombination breakpoints. The other input is a set of rSPR constraint inequalities for any set of pairs of trees. constNJ is consistent and a strict generalization of the neighbor-joining algorithm; it uses the new notion of maximum agreement partitions (MAPs) to assure that the resulting trees satisfy the given rSPR distance constraints.
Xing, Rui; Gao, Qing-Bo; Zhang, Fa-Qi; Fu, Peng-Cheng; Wang, Jiu-Li; Yan, Hui-Ying; Chen, Shi-Long
2017-08-01
Floccularia luteovirens, as an ectomycorrhizal fungus, is widely distributed in the Qinghai-Tibet Plateau. As an edible fungus, it is famous for its unique flavor. Former studies mainly focus on the chemical composition and genetic structure of this species. However, the phylogenetic relationship between genotypes remains unknown. In this study, the genetic variation and phylogenetic relationship between the genotypes of F. luteovirens in Qinghai-Tibet Plateau was estimated through the analysis on two protein-coding genes (rpb1 and ef-1α) from 398 individuals collected from 24 wild populations. The sample covered the entire range of this species during all the growth seasons from 2011 to 2015. 13 genotypes were detected and moderate genetic diversity was revealed. Based on the results of network analysis, the maximum likelihood (ML), maximum parsimony (MP), and Bayesian inference (BI) analyses, the genotypes H-1, H-4, H-6, H-8, H-10, and H-11 were grouped into one clade. Additionally, a relatively higher genotype diversity (average h value is 0.722) and unique genotypes in the northeast edge of Qinghai- Tibet plateau have been found, combined with the results of mismatch analysis and neutrality tests indicated that Southeast Qinghai-Tibet plateau was a refuge for F. luteovirens during the historical geological or climatic events (uplifting of the Qinghai-Tibet Plateau or Last Glacial Maximum). Furthermore, the present distribution of the species on the Qinghai-Tibet plateau has resulted from the recent population expansion. Our findings provide a foundation for the future study of the evolutionary history and the speciation of this species.
Rosas-Valdez, Rogelio; Morrone, Juan J; García-Varela, Martín
2012-08-01
Species of Floridosentis (Acanthocephala) are common parasites of mullets (Mugil spp., Mugilidae) found in tropical marine and brackish water in the Americas. Floridosentis includes 2 species distributed in Mexico, i.e., Floridosentis pacifica, restricted to the Pacific Ocean near Salina Cruz, Oaxaca, and Floridosentis mugilis, distributed along the coast of the Pacific Ocean and the Gulf of Mexico. We sampled 18 populations of F. mugilis and F. pacifica (12 from the Pacific and 6 from the Gulf of Mexico) and sequenced a fragment of the rDNA large subunit to evaluate phylogenetic relationships of populations of Floridosentis spp. from Mexico. Species identification of museum specimens of F. mugilis from the Pacific Ocean was confirmed by examination of morphology traits. Phylogenetic trees inferred with maximum parsimony, maximum likelihood, and Bayesian inference indicate that Floridosentis is monophyletic comprising of 2 major well-supported clades, the first clade corresponding to F. mugilis from the Gulf of Mexico, and the second to F. pacifica from the Pacific Ocean. Genetic divergence between species ranged from 7.68 to 8.60%. Intraspecific divergence ranged from 0.14 to 0.86% for F. mugilis and from 1.72 to 4.49% for F. pacifica. Data obtained from diagnostic characters indicate that specimens from the Pacific Ocean in Mexico have differences in some traits among locations. These results are consistent with the phylogenetic hypothesis, indicating that F. pacifica is distributed in the Pacific Ocean in Mexico with 3 major lineages.
Directory of Open Access Journals (Sweden)
Mariën J
2008-03-01
Full Text Available Abstract Background In recent years, several new hypotheses on phylogenetic relations among arthropods have been proposed on the basis of DNA sequences. One of the challenged hypotheses is the monophyly of hexapods. This discussion originated from analyses based on mitochondrial DNA datasets that, due to an unusual positioning of Collembola, suggested that the hexapod body plan evolved at least twice. Here, we re-evaluate the position of Collembola using ribosomal protein gene sequences. Results In total 48 ribosomal proteins were obtained for the collembolan Folsomia candida. These 48 sequences were aligned with sequence data on 35 other ecdysozoans. Each ribosomal protein gene was available for 25% to 86% of the taxa. However, the total sequence information was unequally distributed over the taxa and ranged between 4% and 100%. A concatenated dataset was constructed (5034 inferred amino acids in length, of which ~66% of the positions were filled. Phylogenetic tree reconstructions, using Maximum Likelihood, Maximum Parsimony, and Bayesian methods, resulted in a topology that supports monophyly of Hexapoda. Conclusion Although ribosomal proteins in general may not evolve independently, they once more appear highly valuable for phylogenetic reconstruction. Our analyses clearly suggest that Hexapoda is monophyletic. This underpins the inconsistency between nuclear and mitochondrial datasets when analyzing pancrustacean relationships. Caution is needed when applying mitochondrial markers in deep phylogeny.
Timmermans, M J T N; Roelofs, D; Mariën, J; van Straalen, N M
2008-03-12
In recent years, several new hypotheses on phylogenetic relations among arthropods have been proposed on the basis of DNA sequences. One of the challenged hypotheses is the monophyly of hexapods. This discussion originated from analyses based on mitochondrial DNA datasets that, due to an unusual positioning of Collembola, suggested that the hexapod body plan evolved at least twice. Here, we re-evaluate the position of Collembola using ribosomal protein gene sequences. In total 48 ribosomal proteins were obtained for the collembolan Folsomia candida. These 48 sequences were aligned with sequence data on 35 other ecdysozoans. Each ribosomal protein gene was available for 25% to 86% of the taxa. However, the total sequence information was unequally distributed over the taxa and ranged between 4% and 100%. A concatenated dataset was constructed (5034 inferred amino acids in length), of which ~66% of the positions were filled. Phylogenetic tree reconstructions, using Maximum Likelihood, Maximum Parsimony, and Bayesian methods, resulted in a topology that supports monophyly of Hexapoda. Although ribosomal proteins in general may not evolve independently, they once more appear highly valuable for phylogenetic reconstruction. Our analyses clearly suggest that Hexapoda is monophyletic. This underpins the inconsistency between nuclear and mitochondrial datasets when analyzing pancrustacean relationships. Caution is needed when applying mitochondrial markers in deep phylogeny.
Essays on empirical likelihood in economics
Gao, Z.
2012-01-01
This thesis intends to exploit the roots of empirical likelihood and its related methods in mathematical programming and computation. The roots will be connected and the connections will induce new solutions for the problems of estimation, computation, and generalization of empirical likelihood.
Enumerating all maximal frequent subtrees in collections of phylogenetic trees.
Deepak, Akshay; Fernández-Baca, David
2014-01-01
A common problem in phylogenetic analysis is to identify frequent patterns in a collection of phylogenetic trees. The goal is, roughly, to find a subset of the species (taxa) on which all or some significant subset of the trees agree. One popular method to do so is through maximum agreement subtrees (MASTs). MASTs are also used, among other things, as a metric for comparing phylogenetic trees, computing congruence indices and to identify horizontal gene transfer events. We give algorithms and experimental results for two approaches to identify common patterns in a collection of phylogenetic trees, one based on agreement subtrees, called maximal agreement subtrees, the other on frequent subtrees, called maximal frequent subtrees. These approaches can return subtrees on larger sets of taxa than MASTs, and can reveal new common phylogenetic relationships not present in either MASTs or the majority rule tree (a popular consensus method). Our current implementation is available on the web at https://code.google.com/p/mfst-miner/. Our computational results confirm that maximal agreement subtrees and all maximal frequent subtrees can reveal a more complete phylogenetic picture of the common patterns in collections of phylogenetic trees than maximum agreement subtrees; they are also often more resolved than the majority rule tree. Further, our experiments show that enumerating maximal frequent subtrees is considerably more practical than enumerating ordinary (not necessarily maximal) frequent subtrees.
Enumerating all maximal frequent subtrees in collections of phylogenetic trees
2014-01-01
Background A common problem in phylogenetic analysis is to identify frequent patterns in a collection of phylogenetic trees. The goal is, roughly, to find a subset of the species (taxa) on which all or some significant subset of the trees agree. One popular method to do so is through maximum agreement subtrees (MASTs). MASTs are also used, among other things, as a metric for comparing phylogenetic trees, computing congruence indices and to identify horizontal gene transfer events. Results We give algorithms and experimental results for two approaches to identify common patterns in a collection of phylogenetic trees, one based on agreement subtrees, called maximal agreement subtrees, the other on frequent subtrees, called maximal frequent subtrees. These approaches can return subtrees on larger sets of taxa than MASTs, and can reveal new common phylogenetic relationships not present in either MASTs or the majority rule tree (a popular consensus method). Our current implementation is available on the web at https://code.google.com/p/mfst-miner/. Conclusions Our computational results confirm that maximal agreement subtrees and all maximal frequent subtrees can reveal a more complete phylogenetic picture of the common patterns in collections of phylogenetic trees than maximum agreement subtrees; they are also often more resolved than the majority rule tree. Further, our experiments show that enumerating maximal frequent subtrees is considerably more practical than enumerating ordinary (not necessarily maximal) frequent subtrees. PMID:25061474
Visualizing phylogenetic tree landscapes.
Wilgenbusch, James C; Huang, Wen; Gallivan, Kyle A
2017-02-02
Genomic-scale sequence alignments are increasingly used to infer phylogenies in order to better understand the processes and patterns of evolution. Different partitions within these new alignments (e.g., genes, codon positions, and structural features) often favor hundreds if not thousands of competing phylogenies. Summarizing and comparing phylogenies obtained from multi-source data sets using current consensus tree methods discards valuable information and can disguise potential methodological problems. Discovery of efficient and accurate dimensionality reduction methods used to display at once in 2- or 3- dimensions the relationship among these competing phylogenies will help practitioners diagnose the limits of current evolutionary models and potential problems with phylogenetic reconstruction methods when analyzing large multi-source data sets. We introduce several dimensionality reduction methods to visualize in 2- and 3-dimensions the relationship among competing phylogenies obtained from gene partitions found in three mid- to large-size mitochondrial genome alignments. We test the performance of these dimensionality reduction methods by applying several goodness-of-fit measures. The intrinsic dimensionality of each data set is also estimated to determine whether projections in 2- and 3-dimensions can be expected to reveal meaningful relationships among trees from different data partitions. Several new approaches to aid in the comparison of different phylogenetic landscapes are presented. Curvilinear Components Analysis (CCA) and a stochastic gradient decent (SGD) optimization method give the best representation of the original tree-to-tree distance matrix for each of the three- mitochondrial genome alignments and greatly outperformed the method currently used to visualize tree landscapes. The CCA + SGD method converged at least as fast as previously applied methods for visualizing tree landscapes. We demonstrate for all three mtDNA alignments that 3D
Directory of Open Access Journals (Sweden)
Talavera Gerard
2011-10-01
Full Text Available Abstract Background Efforts to solve higher-level evolutionary relationships within the class Insecta by using mitochondrial genomic data are hindered due to fast sequence evolution of several groups, most notably Hymenoptera, Strepsiptera, Phthiraptera, Hemiptera and Thysanoptera. Accelerated rates of substitution on their sequences have been shown to have negative consequences in phylogenetic inference. In this study, we tested several methodological approaches to recover phylogenetic signal from whole mitochondrial genomes. As a model, we used two classical problems in insect phylogenetics: The relationships within Paraneoptera and within Holometabola. Moreover, we assessed the mitochondrial phylogenetic signal limits in the deeper Eumetabola dataset, and we studied the contribution of individual genes. Results Long-branch attraction (LBA artefacts were detected in all the datasets. Methods using Bayesian inference outperformed maximum likelihood approaches, and LBA was avoided in Paraneoptera and Holometabola when using protein sequences and the site-heterogeneous mixture model CAT. The better performance of this method was evidenced by resulting topologies matching generally accepted hypotheses based on nuclear and/or morphological data, and was confirmed by cross-validation and simulation analyses. Using the CAT model, the order Strepsiptera was recovered as sister to Coleoptera for the first time using mitochondrial sequences, in agreement with recent results based on large nuclear and morphological datasets. Also the Hymenoptera-Mecopterida association was obtained, leaving Coleoptera and Strepsiptera as the basal groups of the holometabolan insects, which coincides with one of the two main competing hypotheses. For the Paraneroptera, the currently accepted non-monophyly of Homoptera was documented as a phylogenetic novelty for mitochondrial data. However, results were not satisfactory when exploring the entire Eumetabola, revealing the
Davis, Brian W; Li, Gang; Murphy, William J
2010-07-01
The pantherine lineage of cats diverged from the remainder of modern Felidae less than 11 million years ago and consists of the five big cats of the genus Panthera, the lion, tiger, jaguar, leopard, and snow leopard, as well as the closely related clouded leopard. A significant problem exists with respect to the precise phylogeny of these highly threatened great cats. Despite multiple publications on the subject, no two molecular studies have reconstructed Panthera with the same topology. These evolutionary relationships remain unresolved partially due to the recent and rapid radiation of pantherines in the Pliocene, individual speciation events occurring within less than 1 million years, and probable introgression between lineages following their divergence. We provide an alternative, highly supported interpretation of the evolutionary history of the pantherine lineage using novel and published DNA sequence data from the autosomes, both sex chromosomes and the mitochondrial genome. New sequences were generated for 39 single-copy regions of the felid Y chromosome, as well as four mitochondrial and four autosomal gene segments, totaling 28.7 kb. Phylogenetic analysis of these new data, combined with all published data in GenBank, highlighted the prevalence of phylogenetic disparities stemming either from the amplification of a mitochondrial to nuclear translocation event (numt), or errors in species identification. Our 47.6 kb combined dataset was analyzed as a supermatrix and with respect to individual partitions using maximum likelihood and Bayesian phylogenetic inference, in conjunction with Bayesian Estimation of Species Trees (BEST) which accounts for heterogeneous gene histories. Our results yield a robust consensus topology supporting the monophyly of lion and leopard, with jaguar sister to these species, as well as a sister species relationship of tiger and snow leopard. These results highlight new avenues for the study of speciation genomics and
Asymptotic Likelihood Distribution for Correlated & Constrained Systems
Agarwal, Ujjwal
2016-01-01
It describes my work as summer student at CERN. The report discusses the asymptotic distribution of the likelihood ratio for total no. of parameters being h and 2 out of these being are constrained and correlated.
Govindarajulu, Rajanikanth; Hughes, Colin E; Bailey, C Donovan
2011-12-01
Leucaena comprises 17 diploid species, five tetraploid species, and a complex series of hybrids whose evolutionary histories have been influenced by human seed translocation, cultivation, and subsequent spontaneous hybridization. Here we investigated patterns of evolutionary divergence among diploid Leucaena through comprehensively sampled multilocus phylogenetic and population genetic approaches to address species delimitation, interspecific relationships, hybridization, and the predominant mode of speciation among diploids. Parsimony- and maximum-likelihood-based phylogenetic approaches were applied to 59 accessions sequenced for six SCAR-based nuclear loci, nrDNA ITS, and four cpDNA regions. Population genetic comparisons included 1215 AFLP loci representing 42 populations and 424 individuals. Phylogenetic results provided a well-resolved hypothesis of divergent species relationships, recovering previously recognized clades of diploids as well as newly resolved relationships. Phylogenetic and population genetic assessments identified two cryptic species that are consistent with geography and morphology. Findings from this study highlight the importance and utility of multilocus data in the recovery of complex evolutionary histories. The results are consistent with allopatric divergence representing the predominant mode of speciation among diploid Leucaena. These findings contrast with the potential hybrid origin of several tetraploid species and highlight the importance of human translocation of seed to the origin of these tetraploids. The recognition of one previously unrecognized species (L. cruziana) and the elevation of another taxon (L. collinsii subsp. zacapana) to specific status (L. zacapana) is consistent with a growing number of newly diagnosed species from neotropical seasonally dry forests, suggesting these communities harbor greater species diversity than previously recognized.
Performance analysis of linear codes under maximum-likelihood decoding: a tutorial
National Research Council Canada - National Science Library
Sason, Igal; Shamai, Shlomo
2006-01-01
..., upper and lower bounds on the error probability of linear codes under ML decoding are surveyed and applied to codes and ensembles of codes on graphs. For upper bounds, we discuss various bounds where focus is put on Gallager bounding techniques and their relation to a variety of other reported bounds. Within the class of lower bounds, we ad...
Quasi-Maximum-Likelihood Detector Based on Geometrical Diversification Greedy Intensification
Nafkha , Amor; Boutillon , Emmanuel; Roland , Christian
2009-01-01
IEEE Transactions On Communications, vol. 57, n°4, pp. 926-929, April 2009.; International audience; The ML detection used in many communication applications reduces down to solving an integer least-squares problem, which minimizes an objective function. If the matrix is not orthogonal, this problem is NP-hard. An exhaustive search over all feasible solutions is thus only applicable when the dimension of the problem is low. In the literature, there are two main available classes of methods. T...
Can, Seda; van de Schoot, Rens|info:eu-repo/dai/nl/304833207; Hox, Joop|info:eu-repo/dai/nl/073351431
2015-01-01
Because variables may be correlated in the social and behavioral sciences, multicollinearity might be problematic. This study investigates the effect of collinearity manipulated in within and between levels of a two-level confirmatory factor analysis by Monte Carlo simulation. Furthermore, the
Campbell, D A; Chkrebtii, O
2013-12-01
Statistical inference for biochemical models often faces a variety of characteristic challenges. In this paper we examine state and parameter estimation for the JAK-STAT intracellular signalling mechanism, which exemplifies the implementation intricacies common in many biochemical inference problems. We introduce an extension to the Generalized Smoothing approach for estimating delay differential equation models, addressing selection of complexity parameters, choice of the basis system, and appropriate optimization strategies. Motivated by the JAK-STAT system, we further extend the generalized smoothing approach to consider a nonlinear observation process with additional unknown parameters, and highlight how the approach handles unobserved states and unevenly spaced observations. The methodology developed is generally applicable to problems of estimation for differential equation models with delays, unobserved states, nonlinear observation processes, and partially observed histories. Crown Copyright © 2013. Published by Elsevier Inc. All rights reserved.
Analytical maximum-likelihood method to detect patterns in real networks
International Nuclear Information System (INIS)
Squartini, Tiziano; Garlaschelli, Diego
2011-01-01
In order to detect patterns in real networks, randomized graph ensembles that preserve only part of the topology of an observed network are systematically used as fundamental null models. However, the generation of them is still problematic. Existing approaches are either computationally demanding and beyond analytic control or analytically accessible but highly approximate. Here, we propose a solution to this long-standing problem by introducing a fast method that allows one to obtain expectation values and standard deviations of any topological property analytically, for any binary, weighted, directed or undirected network. Remarkably, the time required to obtain the expectation value of any property analytically across the entire graph ensemble is as short as that required to compute the same property using the adjacency matrix of the single original network. Our method reveals that the null behavior of various correlation properties is different from what was believed previously, and is highly sensitive to the particular network considered. Moreover, our approach shows that important structural properties (such as the modularity used in community detection problems) are currently based on incorrect expressions, and provides the exact quantities that should replace them.
Propagation of Statistical Noise Through a Two-Qubit Maximum Likelihood Tomography
2018-04-01
entangled mixed states: creation and concentration. Physical Review Letters. 2004;92(13):133601. 4. White AG et al. Nonmaximally entangled states...production, characterization, and utilization. Physical Review Letters. 1999;83(16):3103. 5. Wang SX, Moraw P, Reilly DR, Altepeter JB, Kanter GS...photon Greenberger-Horne-Zeilinger state using quantum state tomography. Physical Review Letters. 2005;94(7):070402. 7. Mikami H et al. New high
A simple route to maximum-likelihood estimates of two-locus ...
Indian Academy of Sciences (India)
ulation study of their proposed algorithm, and apply it to a dataset given by Clemens .... complicated routes to MLEs are sometimes used in genetic applications when a simpler ... computing, version 3.1.2. R Foundation for Statistical Comput-.
Morales-Casique, E.; Neuman, S.P.; Vesselinov, V.V.
2010-01-01
We use log permeability and porosity data obtained from single-hole pneumatic packer tests in six boreholes drilled into unsaturated fractured tuff near Superior, Arizona, to postulate, calibrate and compare five alternative variogram models (exponential, exponential with linear drift, power,
Digital Repository Service at National Institute of Oceanography (India)
Hassani, V.; Sorensen, A.J.; Pascoal, A.M.
This paper addresses a filtering problem that arises in the design of dynamic positioning systems for ships and offshore rigs subjected to the influence of sea waves. The dynamic model of the vessel captures explicitly the sea state as an uncertain...
Lennington, R. K.; Rassbach, M. E.
1979-01-01
Discussed in this report is the clustering algorithm CLASSY, including detailed descriptions of its general structure and mathematical background and of the various major subroutines. The report provides a development of the logic and equations used with specific reference to program variables. Some comments on timing and proposed optimization techniques are included.
Pilot power optimization for AF relaying using maximum likelihood channel estimation
Wang, Kezhi
2014-09-01
Bit error rates (BERs) for amplify-and-forward (AF) relaying systems with two different pilot-symbol-aided channel estimation methods, disintegrated channel estimation (DCE) and cascaded channel estimation (CCE), are derived in Rayleigh fading channels. Based on these BERs, the pilot powers at the source and at the relay are optimized when their total transmitting powers are fixed. Numerical results show that the optimized system has a better performance than other conventional nonoptimized allocation systems. They also show that the optimal pilot power in variable gain is nearly the same as that in fixed gain for similar system settings. andcopy; 2014 IEEE.
HIROSE,Hideo
1998-01-01
TYPES OF THE DISTRIBUTION:13;Normal distribution (2-parameter)13;Uniform distribution (2-parameter)13;Exponential distribution ( 2-parameter)13;Weibull distribution (2-parameter)13;Gumbel Distribution (2-parameter)13;Weibull/Frechet Distribution (3-parameter)13;Generalized extreme-value distribution (3-parameter)13;Gamma distribution (3-parameter)13;Extended Gamma distribution (3-parameter)13;Log-normal distribution (3-parameter)13;Extended Log-normal distribution (3-parameter)13;Generalized ...
Novel maximum likelihood approach for passive detection and localisation of multiple emitters
Hernandez, Marcel
2017-12-01
In this paper, a novel target acquisition and localisation algorithm (TALA) is introduced that offers a capability for detecting and localising multiple targets using the intermittent "signals-of-opportunity" (e.g. acoustic impulses or radio frequency transmissions) they generate. The TALA is a batch estimator that addresses the complex multi-sensor/multi-target data association problem in order to estimate the locations of an unknown number of targets. The TALA is unique in that it does not require measurements to be of a specific type, and can be implemented for systems composed of either homogeneous or heterogeneous sensors. The performance of the TALA is demonstrated in simulated scenarios with a network of 20 sensors and up to 10 targets. The sensors generate angle-of-arrival (AOA), time-of-arrival (TOA), or hybrid AOA/TOA measurements. It is shown that the TALA is able to successfully detect 83-99% of the targets, with a negligible number of false targets declared. Furthermore, the localisation errors of the TALA are typically within 10% of the errors generated by a "genie" algorithm that is given the correct measurement-to-target associations. The TALA also performs well in comparison with an optimistic Cramér-Rao lower bound, with typical differences in performance of 10-20%, and differences in performance of 40-50% in the most difficult scenarios considered. The computational expense of the TALA is also controllable, which allows the TALA to maintain computational feasibility even in the most challenging scenarios considered. This allows the approach to be implemented in time-critical scenarios, such as in the localisation of artillery firing events. It is concluded that the TALA provides a powerful situational awareness aid for passive surveillance operations.
A framelet-based iterative maximum-likelihood reconstruction algorithm for spectral CT
Wang, Yingmei; Wang, Ge; Mao, Shuwei; Cong, Wenxiang; Ji, Zhilong; Cai, Jian-Feng; Ye, Yangbo
2016-11-01
Standard computed tomography (CT) cannot reproduce spectral information of an object. Hardware solutions include dual-energy CT which scans the object twice in different x-ray energy levels, and energy-discriminative detectors which can separate lower and higher energy levels from a single x-ray scan. In this paper, we propose a software solution and give an iterative algorithm that reconstructs an image with spectral information from just one scan with a standard energy-integrating detector. The spectral information obtained can be used to produce color CT images, spectral curves of the attenuation coefficient μ (r,E) at points inside the object, and photoelectric images, which are all valuable imaging tools in cancerous diagnosis. Our software solution requires no change on hardware of a CT machine. With the Shepp-Logan phantom, we have found that although the photoelectric and Compton components were not perfectly reconstructed, their composite effect was very accurately reconstructed as compared to the ground truth and the dual-energy CT counterpart. This means that our proposed method has an intrinsic benefit in beam hardening correction and metal artifact reduction. The algorithm is based on a nonlinear polychromatic acquisition model for x-ray CT. The key technique is a sparse representation of iterations in a framelet system. Convergence of the algorithm is studied. This is believed to be the first application of framelet imaging tools to a nonlinear inverse problem.
Estimating Water Demand in Urban Indonesia: A Maximum Likelihood Approach to block Rate Pricing Data
Rietveld, Piet; Rouwendal, Jan; Zwart, Bert
1997-01-01
In this paper the Burtless and Hausman model is used to estimate water demand in Salatiga, Indonesia. Other statistical models, as OLS and IV, are found to be inappropiate. A topic, which does not seem to appear in previous studies, is the fact that the density function of the loglikelihood can be
Maximum likelihood PSD estimation for speech enhancement in reverberant and noisy conditions
DEFF Research Database (Denmark)
Kuklasinski, Adam; Doclo, Simon; Jensen, Jesper
2016-01-01
of the estimator is in speech enhancement algorithms, such as the Multi-channel Wiener Filter (MWF) and the Minimum Variance Distortionless Response (MVDR) beamformer. We evaluate these two algorithms in a speech dereverberation task and compare the performance obtained using the proposed and a competing PSD...... estimator. Instrumental performance measures indicate an advantage of the proposed estimator over the competing one. In a speech intelligibility test all algorithms significantly improved the word intelligibility score. While the results suggest a minor advantage of using the proposed PSD estimator...
C. Zhou (Chen)
2008-01-01
textabstractIn the 18th century, statisticians sometimes worked as consultants to gamblers. In order to answer questions like "If a fair coin is flipped 100 times, what is the probability of getting 60 or more heads?", Abraham de Moivre discovered the so-called "normal curve". Independently,
Directional maximum likelihood self-estimation of the path-loss exponent
Hu, Y.; Leus, G.J.T.; Dong, Min; Zheng, Thomas Fang
2016-01-01
The path-loss exponent (PLE) is a key parameter in wireless propagation channels. Therefore, obtaining the knowledge of the PLE is rather significant for assisting wireless communications and networking to achieve a better performance. Most existing methods for estimating the PLE not only require
Regional compensation for statistical maximum likelihood reconstruction error of PET image pixels
International Nuclear Information System (INIS)
Forma, J; Ruotsalainen, U; Niemi, J A
2013-01-01
In positron emission tomography (PET), there is an increasing interest in studying not only the regional mean tracer concentration, but its variation arising from local differences in physiology, the tissue heterogeneity. However, in reconstructed images this physiological variation is shadowed by a large reconstruction error, which is caused by noisy data and the inversion of tomographic problem. We present a new procedure which can quantify the error variation in regional reconstructed values for given PET measurement, and reveal the remaining tissue heterogeneity. The error quantification is made by creating and reconstructing the noise realizations of virtual sinograms, which are statistically similar with the measured sinogram. Tests with physical phantom data show that the characterization of error variation and the true heterogeneity are possible, despite the existing model error when real measurement is considered. (paper)
Lee, In Heok
2012-01-01
Researchers in career and technical education often ignore more effective ways of reporting and treating missing data and instead implement traditional, but ineffective, missing data methods (Gemici, Rojewski, & Lee, 2012). The recent methodological, and even the non-methodological, literature has increasingly emphasized the importance of…
An Alternative Estimator for the Maximum Likelihood Estimator for the Two Extreme Response Patterns.
1981-06-29
is the item discrimination parameter and b is the g X g item response difficulty parameter which satisfies (2.3) - = b 0 < b1 < b 2 < ....... < b...Tuscon, AZ 85721 4833 Rugby Avenue Dr. John B. Carroll Bethesda, MD 20014 Psychometric Lab 1 Dr. Leonard Feldt Univ. of No. Carolina Lindquist Center for
The early maximum likelihood estimation model of audiovisual integration in speech perception
DEFF Research Database (Denmark)
Andersen, Tobias
2015-01-01
integration to speech perception along with three model variations. In early MLE, integration is based on a continuous internal representation before categorization, which can make the model more parsimonious by imposing constraints that reflect experimental designs. The study also shows that cross......Speech perception is facilitated by seeing the articulatory mouth movements of the talker. This is due to perceptual audiovisual integration, which also causes the McGurk−MacDonald illusion, and for which a comprehensive computational account is still lacking. Decades of research have largely......-validation can evaluate models of audiovisual integration based on typical data sets taking both goodness-of-fit and model flexibility into account. All models were tested on a published data set previously used for testing the FLMP. Cross-validation favored the early MLE while more conventional error measures...
International Nuclear Information System (INIS)
Llacer, J.; Veklerov, E.
1987-05-01
We review our recent work characterizing the image reconstruction properties of the MLE algorithm. We studied its convergence properties and confirmed the onset of image deterioration, which is a function of the number of counts in the source. By modulating the weight given to projection tubes with high numbers of counts with respect to those with low numbers of counts in the reconstruction process, we have confirmed that image deterioration is due to an attempt by the algorithm to match projection data tubes with high numbers of counts too closely to the iterative image projections. We developed a stopping rule for the algorithm that tests the hypothesis that a reconstructed image could have given the initial projection data in a manner consistent with the underlying assumption of Poisson distributed variables. The rule was applied to two mathematically generated phantoms with success and to a third phantom with exact (no statistical fluctuations) projection data. We conclude that the behavior of the target functions whose extrema are sought in iterative schemes is more important in the early stages of the reconstruction than in the later stages, when the extrema are being approached but with the Poisson nature of the measurement. 11 refs., 14 figs
Exact sampling from conditional Boolean models with applications to maximum likelihood inference
Lieshout, van M.N.M.; Zwet, van E.W.
2001-01-01
We are interested in estimating the intensity parameter of a Boolean model of discs (the bombing model) from a single realization. To do so, we derive the conditional distribution of the points (germs) of the underlying Poisson process. We demonstrate how to apply coupling from the past to generate
Jeffrey H. Gove
2003-01-01
Many of the most popular sampling schemes used in forestry are probability proportional to size methods. These methods are also referred to as size biased because sampling is actually from a weighted form of the underlying population distribution. Length- and area-biased sampling are special cases of size-biased sampling where the probability weighting comes from a...
Fast phylogenetic DNA barcoding
DEFF Research Database (Denmark)
Terkelsen, Kasper Munch; Boomsma, Wouter Krogh; Willerslev, Eske
2008-01-01
We present a heuristic approach to the DNA assignment problem based on phylogenetic inferences using constrained neighbour joining and non-parametric bootstrapping. We show that this method performs as well as the more computationally intensive full Bayesian approach in an analysis of 500 insect...... DNA sequences obtained from GenBank. We also analyse a previously published dataset of environmental DNA sequences from soil from New Zealand and Siberia, and use these data to illustrate the fact that statistical approaches to the DNA assignment problem allow for more appropriate criteria...... for determining the taxonomic level at which a particular DNA sequence can be assigned....
International Nuclear Information System (INIS)
Anon.
1979-01-01
This chapter presents a historic overview of the establishment of radiation guidelines by various national and international agencies. The use of maximum permissible dose and maximum permissible body burden limits to derive working standards is discussed
Likelihood Estimation of Gamma Ray Bursts Duration Distribution
Horvath, Istvan
2005-01-01
Two classes of Gamma Ray Bursts have been identified so far, characterized by T90 durations shorter and longer than approximately 2 seconds. It was shown that the BATSE 3B data allow a good fit with three Gaussian distributions in log T90. In the same Volume in ApJ. another paper suggested that the third class of GRBs is may exist. Using the full BATSE catalog here we present the maximum likelihood estimation, which gives us 0.5% probability to having only two subclasses. The MC simulation co...
de Queiroz, Kevin; Poe, Steven
2003-06-01
Kluge's (2001, Syst. Biol. 50:322-330) continued arguments that phylogenetic methods based on the statistical principle of likelihood are incompatible with the philosophy of science described by Karl Popper are based on false premises related to Kluge's misrepresentations of Popper's philosophy. Contrary to Kluge's conjectures, likelihood methods are not inherently verificationist; they do not treat every instance of a hypothesis as confirmation of that hypothesis. The historical nature of phylogeny does not preclude phylogenetic hypotheses from being evaluated using the probability of evidence. The low absolute probabilities of hypotheses are irrelevant to the correct interpretation of Popper's concept termed degree of corroboration, which is defined entirely in terms of relative probabilities. Popper did not advocate minimizing background knowledge; in any case, the background knowledge of both parsimony and likelihood methods consists of the general assumption of descent with modification and additional assumptions that are deterministic, concerning which tree is considered most highly corroborated. Although parsimony methods do not assume (in the sense of entailing) that homoplasy is rare, they do assume (in the sense of requiring to obtain a correct phylogenetic inference) certain things about patterns of homoplasy. Both parsimony and likelihood methods assume (in the sense of implying by the manner in which they operate) various things about evolutionary processes, although violation of those assumptions does not always cause the methods to yield incorrect phylogenetic inferences. Test severity is increased by sampling additional relevant characters rather than by character reanalysis, although either interpretation is compatible with the use of phylogenetic likelihood methods. Neither parsimony nor likelihood methods assess test severity (critical evidence) when used to identify a most highly corroborated tree(s) based on a single method or model and a
A molecular phylogenetic analysis of the Scarabaeinae (dung beetles).
Monaghan, Michael T; Inward, Daegan J G; Hunt, Toby; Vogler, Alfried P
2007-11-01
The dung beetles (Scarabaeinae) include ca. 5000 species and exhibit a diverse array of morphologies and behaviors. This variation presumably reflects the adaptation to a diversity of food types and the different strategies used to avoid competition for vertebrate dung, which is the primary breeding environment for most species. The current classification gives great weight to the major behavioral types, separating the ball rollers and the tunnelers, but existing phylogenetic studies have been based on limited taxonomic or biogeographic sampling and have been contradictory. Here, we present a molecular phylogenetic analysis of 214 species of Scarabaeinae, representing all 12 traditionally recognized tribes and six biogeographical regions, using partial gene sequences from one nuclear (28S) and two mitochondrial (cox1, rrnL) genes. Length variation in 28S (588-621 bp) and rrnL (514-523 bp) was subjected to a thorough evaluation of alternative alignments, gap-coding methods, and tree searches using model-based (Bayesian and likelihood), maximum parsimony, and direct optimization analyses. The small-bodied, non-dung-feeding Sarophorus+Coptorhina were basal in all reconstructions. These were closely related to rolling Odontoloma+Dicranocara, suggesting an early acquisition of rolling behavior. Smaller tribes and most genera were monophyletic, while Canthonini and Dichotomiini each consisted of multiple paraphyletic lineages at hierarchical levels equivalent to the smaller tribes. Plasticity of rolling and tunneling was evidenced by a lack of monophyly (S-H test, p > 0.05) and several reversals within clades. The majority of previously unrecognized clades were geographical, including the well-supported Neotropical Phanaeini+Eucraniini, and a large Australian clade of rollers as well as tunneling Coptodactyla and Demarziella. Only three lineages, Gymnopleurini, Copris+Microcopris and Onthophagus, were widespread and therefore appear to be dispersive at a global scale. A
Phylogenetic trees in bioinformatics
Energy Technology Data Exchange (ETDEWEB)
Burr, Tom L [Los Alamos National Laboratory
2008-01-01
Genetic data is often used to infer evolutionary relationships among a collection of viruses, bacteria, animal or plant species, or other operational taxonomic units (OTU). A phylogenetic tree depicts such relationships and provides a visual representation of the estimated branching order of the OTUs. Tree estimation is unique for several reasons, including: the types of data used to represent each OTU; the use ofprobabilistic nucleotide substitution models; the inference goals involving both tree topology and branch length, and the huge number of possible trees for a given sample of a very modest number of OTUs, which implies that fmding the best tree(s) to describe the genetic data for each OTU is computationally demanding. Bioinformatics is too large a field to review here. We focus on that aspect of bioinformatics that includes study of similarities in genetic data from multiple OTUs. Although research questions are diverse, a common underlying challenge is to estimate the evolutionary history of the OTUs. Therefore, this paper reviews the role of phylogenetic tree estimation in bioinformatics, available methods and software, and identifies areas for additional research and development.
Maximum entropy analysis of EGRET data
DEFF Research Database (Denmark)
Pohl, M.; Strong, A.W.
1997-01-01
EGRET data are usually analysed on the basis of the Maximum-Likelihood method \\cite{ma96} in a search for point sources in excess to a model for the background radiation (e.g. \\cite{hu97}). This method depends strongly on the quality of the background model, and thus may have high systematic unce...... uncertainties in region of strong and uncertain background like the Galactic Center region. Here we show images of such regions obtained by the quantified Maximum-Entropy method. We also discuss a possible further use of MEM in the analysis of problematic regions of the sky....
Density estimation by maximum quantum entropy
International Nuclear Information System (INIS)
Silver, R.N.; Wallstrom, T.; Martz, H.F.
1993-01-01
A new Bayesian method for non-parametric density estimation is proposed, based on a mathematical analogy to quantum statistical physics. The mathematical procedure is related to maximum entropy methods for inverse problems and image reconstruction. The information divergence enforces global smoothing toward default models, convexity, positivity, extensivity and normalization. The novel feature is the replacement of classical entropy by quantum entropy, so that local smoothing is enforced by constraints on differential operators. The linear response of the estimate is proportional to the covariance. The hyperparameters are estimated by type-II maximum likelihood (evidence). The method is demonstrated on textbook data sets
Koepfli, Klaus-Peter; Wayne, Robert K
2003-10-01
We compared the utility of five nuclear gene segments amplified with type I sequence-tagged site (STS) primers versus the complete mitochondrial cytochrome b (cyt b) gene in resolving phylogenetic relationships within the Mustelidae, a large and ecomorphologically diverse family of mammalian carnivores. Maximum parsimony and likelihood analyses of separate and combined data sets were used to address questions regarding the levels of homoplasy, incongruence, and information content within and among loci. All loci showed limited resolution in the separate analyses because of either a low amount of informative variation (nuclear genes) or high levels of homoplasy (cyt b). Individually or combined, the nuclear gene sequences had less homoplasy, retained more signal, and were more decisive, even though cyt b contained more potentially informative variation than all the nuclear sequences combined. We obtained a well-resolved and supported phylogeny when the nuclear sequences were combined. Maximum likelihood and Bayesian phylogenetic analyses of the total combined data (nuclear and mitochondrial DNA sequences) were able to better accommodate the high levels of homoplasy in the cyt b data than was an equally weighted maximum parsimony analysis. Furthermore, partition Bremer support analyses of the total combined tree showed that the relative support of the nuclear and mitochondrial genes differed according to whether or not the homoplasy in the cyt b gene was downweighted. Although the cyt b gene contributed phylogenetic signal for most major groupings, the nuclear gene sequences were more effective in reconstructing the deeper nodes of the combined tree in the equally weighted parsimony analysis, as judged by the variable-length bootstrap method. The total combined data supported the monophyly of the Lutrinae (otters), whereas the Melinae (badgers) and Mustelinae (weasels, martens) were both paraphyletic. The American badger, Taxidea taxus (Taxidiinae), was the most