Algorithms of maximum likelihood data clustering with applications

Science.gov (United States)

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.

The one-sided Ap conditions and local maximal operator

Czech Academy of Sciences Publication Activity Database

Bernardis, A.L.; Gogatishvili, Amiran; Martin-Reyes, F. J.; Ortega Salvador, P.; Pick, L.

Roč. 55, č. 1 ( 2012 ), s. 79-104 ISSN 0013-0915 R&D Projects: GA ČR GA201/08/0383; GA ČR GA201/05/2033 Institutional research plan: CEZ:AV0Z10190503 Keywords : one-sided Ap conditions * one-sided local maximal operator * quasi-Banach function spaces * variable-exponent Lebesgue spaces Subject RIV: BA - General Mathematics Impact factor: 0.561, year: 2012 http://journals.cambridge.org/action/displayAbstract?fromPage=online&aid=8477114&fulltextType=RA&fileId=S0013091510000635

Maximum Likelihood Method for Predicting Environmental Conditions from Assemblage Composition: The R Package bio.infer

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.

IRT Item Parameter Recovery with Marginal Maximum Likelihood Estimation Using Loglinear Smoothing Models

Science.gov (United States)

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…

Generalized linear models with random effects unified analysis via H-likelihood

CERN Document Server

Lee, Youngjo; Pawitan, Yudi

2006-01-01

Since their introduction in 1972, generalized linear models (GLMs) have proven useful in the generalization of classical normal models. Presenting methods for fitting GLMs with random effects to data, Generalized Linear Models with Random Effects: Unified Analysis via H-likelihood explores a wide range of applications, including combining information over trials (meta-analysis), analysis of frailty models for survival data, genetic epidemiology, and analysis of spatial and temporal models with correlated errors.Written by pioneering authorities in the field, this reference provides an introduction to various theories and examines likelihood inference and GLMs. The authors show how to extend the class of GLMs while retaining as much simplicity as possible. By maximizing and deriving other quantities from h-likelihood, they also demonstrate how to use a single algorithm for all members of the class, resulting in a faster algorithm as compared to existing alternatives. Complementing theory with examples, many of...

Implications of maximal Jarlskog invariant and maximal CP violation

International Nuclear Information System (INIS)

Rodriguez-Jauregui, E.; Universidad Nacional Autonoma de Mexico

2001-04-01

We argue here why CP violating phase Φ in the quark mixing matrix is maximal, that is, Φ=90 . In the Standard Model CP violation is related to the Jarlskog invariant J, which can be obtained from non commuting Hermitian mass matrices. In this article we derive the conditions to have Hermitian mass matrices which give maximal Jarlskog invariant J and maximal CP violating phase Φ. We find that all squared moduli of the quark mixing elements have a singular point when the CP violation phase Φ takes the value Φ=90 . This special feature of the Jarlskog invariant J and the quark mixing matrix is a clear and precise indication that CP violating Phase Φ is maximal in order to let nature treat democratically all of the quark mixing matrix moduli. (orig.)

Likelihood Approximation With Parallel Hierarchical Matrices For Large Spatial Datasets

KAUST Repository

Litvinenko, Alexander; Sun, Ying; Genton, Marc G.; Keyes, David E.

2017-01-01

The main goal of this article is to introduce the parallel hierarchical matrix library HLIBpro to the statistical community. We describe the HLIBCov package, which is an extension of the HLIBpro library for approximating large covariance matrices and maximizing likelihood functions. We show that an approximate Cholesky factorization of a dense matrix of size $2M\\times 2M$ can be computed on a modern multi-core desktop in few minutes. Further, HLIBCov is used for estimating the unknown parameters such as the covariance length, variance and smoothness parameter of a Matérn covariance function by maximizing the joint Gaussian log-likelihood function. The computational bottleneck here is expensive linear algebra arithmetics due to large and dense covariance matrices. Therefore covariance matrices are approximated in the hierarchical ($\\H$-) matrix format with computational cost $\\mathcal{O}(k^2n \\log^2 n/p)$ and storage $\\mathcal{O}(kn \\log n)$, where the rank $k$ is a small integer (typically $k<25$), $p$ the number of cores and $n$ the number of locations on a fairly general mesh. We demonstrate a synthetic example, where the true values of known parameters are known. For reproducibility we provide the C++ code, the documentation, and the synthetic data.

Likelihood Approximation With Parallel Hierarchical Matrices For Large Spatial Datasets

KAUST Repository

Litvinenko, Alexander

2017-11-01

The main goal of this article is to introduce the parallel hierarchical matrix library HLIBpro to the statistical community. We describe the HLIBCov package, which is an extension of the HLIBpro library for approximating large covariance matrices and maximizing likelihood functions. We show that an approximate Cholesky factorization of a dense matrix of size $2M\\\\times 2M$ can be computed on a modern multi-core desktop in few minutes. Further, HLIBCov is used for estimating the unknown parameters such as the covariance length, variance and smoothness parameter of a Matérn covariance function by maximizing the joint Gaussian log-likelihood function. The computational bottleneck here is expensive linear algebra arithmetics due to large and dense covariance matrices. Therefore covariance matrices are approximated in the hierarchical ($\\\\H$-) matrix format with computational cost $\\\\mathcal{O}(k^2n \\\\log^2 n/p)$ and storage $\\\\mathcal{O}(kn \\\\log n)$, where the rank $k$ is a small integer (typically $k<25$), $p$ the number of cores and $n$ the number of locations on a fairly general mesh. We demonstrate a synthetic example, where the true values of known parameters are known. For reproducibility we provide the C++ code, the documentation, and the synthetic data.

The bilateral movement condition facilitates maximal but not submaximal paretic-limb grip force in people with post-stroke hemiparesis

Science.gov (United States)

DeJong, Stacey L.; Lang, Catherine E.

2012-01-01

Objectives Although healthy individuals have less force production capacity during bilateral muscle contractions compared to unilateral efforts, emerging evidence suggests that certain aspects of paretic upper limb task performance after stroke may be enhanced by moving bilaterally instead of unilaterally. We investigated whether the bilateral movement condition affects grip force differently on the paretic side of people with post-stroke hemiparesis, compared to their non-paretic side and both sides of healthy young adults. Methods Within a single session, we compared: 1) maximal grip force during unilateral vs. bilateral contractions on each side, and 2) force contributed by each side during a 30% submaximal bilateral contraction. Results Healthy controls produced less grip force in the bilateral condition, regardless of side (- 2.4% difference), and similar findings were observed on the non-paretic side of people with hemiparesis (- 4.5% difference). On the paretic side, however, maximal grip force was increased by the bilateral condition in most participants (+11.3% difference, on average). During submaximal bilateral contractions in each group, the two sides each contributed the same percentage of unilateral maximal force. Conclusions The bilateral condition facilitates paretic limb grip force at maximal, but not submaximal levels. Significance In some people with post-stroke hemiparesis, the paretic limb may benefit from bilateral training with high force requirements. PMID:22248812

The equivalence of information-theoretic and likelihood-based methods for neural dimensionality reduction.

Directory of Open Access Journals (Sweden)

Ross S Williamson

2015-04-01

Full Text Available Stimulus dimensionality-reduction methods in neuroscience seek to identify a low-dimensional space of stimulus features that affect a neuron's probability of spiking. One popular method, known as maximally informative dimensions (MID, uses an information-theoretic quantity known as "single-spike information" to identify this space. Here we examine MID from a model-based perspective. We show that MID is a maximum-likelihood estimator for the parameters of a linear-nonlinear-Poisson (LNP model, and that the empirical single-spike information corresponds to the normalized log-likelihood under a Poisson model. This equivalence implies that MID does not necessarily find maximally informative stimulus dimensions when spiking is not well described as Poisson. We provide several examples to illustrate this shortcoming, and derive a lower bound on the information lost when spiking is Bernoulli in discrete time bins. To overcome this limitation, we introduce model-based dimensionality reduction methods for neurons with non-Poisson firing statistics, and show that they can be framed equivalently in likelihood-based or information-theoretic terms. Finally, we show how to overcome practical limitations on the number of stimulus dimensions that MID can estimate by constraining the form of the non-parametric nonlinearity in an LNP model. We illustrate these methods with simulations and data from primate visual cortex.

Efficient Detection of Repeating Sites to Accelerate Phylogenetic Likelihood Calculations.

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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.

General conditions for maximal violation of non-contextuality in discrete and continuous variables

International Nuclear Information System (INIS)

Laversanne-Finot, A; Ketterer, A; Coudreau, T; Keller, A; Milman, P; Barros, M R; Walborn, S P

2017-01-01

The contextuality of quantum mechanics can be shown by the violation of inequalities based on measurements of well chosen observables. An important property of such observables is that their expectation value can be expressed in terms of probabilities for obtaining two exclusive outcomes. Examples of such inequalities have been constructed using either observables with a dichotomic spectrum or using periodic functions obtained from displacement operators in phase space. Here we identify the general conditions on the spectral decomposition of observables demonstrating state independent contextuality of quantum mechanics. Our results not only unify existing strategies for maximal violation of state independent non-contextuality inequalities but also lead to new scenarios enabling such violations. Among the consequences of our results is the impossibility of having a state independent maximal violation of non-contextuality in the Peres–Mermin scenario with discrete observables of odd dimensions. (paper)

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

Maximum Likelihood and Restricted Likelihood Solutions in Multiple-Method Studies.

Science.gov (United States)

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.

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....

HLIBCov: Parallel Hierarchical Matrix Approximation of Large Covariance Matrices and Likelihoods with Applications in Parameter Identification

KAUST Repository

Litvinenko, Alexander

2017-01-01

and maximizing likelihood functions. We show that an approximate Cholesky factorization of a dense matrix of size $2M\\times 2M$ can be computed on a modern multi-core desktop in few minutes. Further, HLIBCov is used for estimating the unknown parameters

Posterior distributions for likelihood ratios in forensic science.

Science.gov (United States)

van den Hout, Ardo; Alberink, Ivo

2016-09-01

Evaluation of evidence in forensic science is discussed using posterior distributions for likelihood ratios. Instead of eliminating the uncertainty by integrating (Bayes factor) or by conditioning on parameter values, uncertainty in the likelihood ratio is retained by parameter uncertainty derived from posterior distributions. A posterior distribution for a likelihood ratio can be summarised by the median and credible intervals. Using the posterior mean of the distribution is not recommended. An analysis of forensic data for body height estimation is undertaken. The posterior likelihood approach has been criticised both theoretically and with respect to applicability. This paper addresses the latter and illustrates an interesting application area. Copyright © 2016 The Chartered Society of Forensic Sciences. Published by Elsevier Ireland Ltd. All rights reserved.

Does mental exertion alter maximal muscle activation?

Directory of Open Access Journals (Sweden)

Vianney eRozand

2014-09-01

Full Text Available Mental exertion is known to impair endurance performance, but its effects on neuromuscular function remain unclear. The purpose of this study was to test the hypothesis that mental exertion reduces torque and muscle activation during intermittent maximal voluntary contractions of the knee extensors. Ten subjects performed in a randomized order three separate mental exertion conditions lasting 27 minutes each: i high mental exertion (incongruent Stroop task, ii moderate mental exertion (congruent Stroop task, iii low mental exertion (watching a movie. In each condition, mental exertion was combined with ten intermittent maximal voluntary contractions of the knee extensor muscles (one maximal voluntary contraction every 3 minutes. Neuromuscular function was assessed using electrical nerve stimulation. Maximal voluntary torque, maximal muscle activation and other neuromuscular parameters were similar across mental exertion conditions and did not change over time. These findings suggest that mental exertion does not affect neuromuscular function during intermittent maximal voluntary contractions of the knee extensors.

Accelerated maximum likelihood parameter estimation for stochastic biochemical systems

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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

Zero-inflated Poisson model based likelihood ratio test for drug safety signal detection.

Science.gov (United States)

Huang, Lan; Zheng, Dan; Zalkikar, Jyoti; Tiwari, Ram

2017-02-01

In recent decades, numerous methods have been developed for data mining of large drug safety databases, such as Food and Drug Administration's (FDA's) Adverse Event Reporting System, where data matrices are formed by drugs such as columns and adverse events as rows. Often, a large number of cells in these data matrices have zero cell counts and some of them are "true zeros" indicating that the drug-adverse event pairs cannot occur, and these zero counts are distinguished from the other zero counts that are modeled zero counts and simply indicate that the drug-adverse event pairs have not occurred yet or have not been reported yet. In this paper, a zero-inflated Poisson model based likelihood ratio test method is proposed to identify drug-adverse event pairs that have disproportionately high reporting rates, which are also called signals. The maximum likelihood estimates of the model parameters of zero-inflated Poisson model based likelihood ratio test are obtained using the expectation and maximization algorithm. The zero-inflated Poisson model based likelihood ratio test is also modified to handle the stratified analyses for binary and categorical covariates (e.g. gender and age) in the data. The proposed zero-inflated Poisson model based likelihood ratio test method is shown to asymptotically control the type I error and false discovery rate, and its finite sample performance for signal detection is evaluated through a simulation study. The simulation results show that the zero-inflated Poisson model based likelihood ratio test method performs similar to Poisson model based likelihood ratio test method when the estimated percentage of true zeros in the database is small. Both the zero-inflated Poisson model based likelihood ratio test and likelihood ratio test methods are applied to six selected drugs, from the 2006 to 2011 Adverse Event Reporting System database, with varying percentages of observed zero-count cells.

Automatic physical inference with information maximizing neural networks

Science.gov (United States)

Charnock, Tom; Lavaux, Guilhem; Wandelt, Benjamin D.

2018-04-01

Compressing large data sets to a manageable number of summaries that are informative about the underlying parameters vastly simplifies both frequentist and Bayesian inference. When only simulations are available, these summaries are typically chosen heuristically, so they may inadvertently miss important information. We introduce a simulation-based machine learning technique that trains artificial neural networks to find nonlinear functionals of data that maximize Fisher information: information maximizing neural networks (IMNNs). In test cases where the posterior can be derived exactly, likelihood-free inference based on automatically derived IMNN summaries produces nearly exact posteriors, showing that these summaries are good approximations to sufficient statistics. In a series of numerical examples of increasing complexity and astrophysical relevance we show that IMNNs are robustly capable of automatically finding optimal, nonlinear summaries of the data even in cases where linear compression fails: inferring the variance of Gaussian signal in the presence of noise, inferring cosmological parameters from mock simulations of the Lyman-α forest in quasar spectra, and inferring frequency-domain parameters from LISA-like detections of gravitational waveforms. In this final case, the IMNN summary outperforms linear data compression by avoiding the introduction of spurious likelihood maxima. We anticipate that the automatic physical inference method described in this paper will be essential to obtain both accurate and precise cosmological parameter estimates from complex and large astronomical data sets, including those from LSST and Euclid.

Direct reconstruction of the source intensity distribution of a clinical linear accelerator using a maximum likelihood expectation maximization algorithm.

Science.gov (United States)

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.

Applications of expectation maximization algorithm for coherent optical communication

DEFF Research Database (Denmark)

Carvalho, L.; Oliveira, J.; Zibar, Darko

2014-01-01

In this invited paper, we present powerful statistical signal processing methods, used by machine learning community, and link them to current problems in optical communication. In particular, we will look into iterative maximum likelihood parameter estimation based on expectation maximization...... algorithm and its application in coherent optical communication systems for linear and nonlinear impairment mitigation. Furthermore, the estimated parameters are used to build the probabilistic model of the system for the synthetic impairment generation....

Interpopulational Variations in Sexual Chemical Signals of Iberian Wall Lizards May Allow Maximizing Signal Efficiency under Different Climatic Conditions.

Science.gov (United States)

Martín, José; Ortega, Jesús; López, Pilar

2015-01-01

Sexual signals used in intraspecific communication are expected to evolve to maximize efficacy under a given climatic condition. Thus, chemical secretions of lizards might evolve in the evolutionary time to ensure that signals are perfectly tuned to local humidity and temperature conditions affecting their volatility and therefore their persistence and transmission through the environment. We tested experimentally whether interpopulational altitudinal differences in chemical composition of femoral gland secretions of male Iberian wall lizards (Podarcis hispanicus) have evolved to maximize efficacy of chemical signals in different environmental conditions. Chemical analyses first showed that the characteristics of chemical signals of male lizards differed between two populations inhabiting environments with different climatic conditions in spite of the fact that these two populations are closely related genetically. We also examined experimentally whether the temporal attenuation of the chemical stimuli depended on simulated climatic conditions. Thus, we used tongue-flick essays to test whether female lizards were able to detect male scent marks maintained under different conditions of temperature and humidity by chemosensory cues alone. Chemosensory tests showed that chemical signals of males had a lower efficacy (i.e. detectability and persistence) when temperature and dryness increase, but that these effects were more detrimental for signals of the highest elevation population, which occupies naturally colder and more humid environments. We suggest that the abiotic environment may cause a selective pressure on the form and expression of sexual chemical signals. Therefore, interpopulational differences in chemical profiles of femoral secretions of male P. hispanicus lizards may reflect adaptation to maximize the efficacy of the chemical signal in different climates.

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

Likelihood inference for a nonstationary fractional autoregressive model

DEFF Research Database (Denmark)

Johansen, Søren; Ørregård Nielsen, Morten

2010-01-01

This paper discusses model-based inference in an autoregressive model for fractional processes which allows the process to be fractional of order d or d-b. Fractional differencing involves infinitely many past values and because we are interested in nonstationary processes we model the data X1......,...,X_{T} given the initial values X_{-n}, n=0,1,..., as is usually done. The initial values are not modeled but assumed to be bounded. This represents a considerable generalization relative to all previous work where it is assumed that initial values are zero. For the statistical analysis we assume...... the conditional Gaussian likelihood and for the probability analysis we also condition on initial values but assume that the errors in the autoregressive model are i.i.d. with suitable moment conditions. We analyze the conditional likelihood and its derivatives as stochastic processes in the parameters, including...

Empirical likelihood

CERN Document Server

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...

Approximate Likelihood

CERN Multimedia

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...

Cases in which ancestral maximum likelihood will be confusingly misleading.

Science.gov (United States)

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.

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)

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.

Likelihood inference for a fractionally cointegrated vector autoregressive model

DEFF Research Database (Denmark)

Johansen, Søren; Ørregård Nielsen, Morten

2012-01-01

such that the process X_{t} is fractional of order d and cofractional of order d-b; that is, there exist vectors ß for which ß'X_{t} is fractional of order d-b, and no other fractionality order is possible. We define the statistical model by 0inference when the true values satisfy b0¿1/2 and d0-b0......We consider model based inference in a fractionally cointegrated (or cofractional) vector autoregressive model with a restricted constant term, ¿, based on the Gaussian likelihood conditional on initial values. The model nests the I(d) VAR model. We give conditions on the parameters...... process in the parameters when errors are i.i.d. with suitable moment conditions and initial values are bounded. When the limit is deterministic this implies uniform convergence in probability of the conditional likelihood function. If the true value b0>1/2, we prove that the limit distribution of (ß...

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

Simplified likelihood for the re-interpretation of public CMS results

CERN Document Server

The CMS Collaboration

2017-01-01

In this note, a procedure for the construction of simplified likelihoods for the re-interpretation of the results of CMS searches for new physics is presented. The procedure relies on the use of a reduced set of information on the background models used in these searches which can readily be provided by the CMS collaboration. A toy example is used to demonstrate the procedure and its accuracy in reproducing the full likelihood for setting limits in models for physics beyond the standard model. Finally, two representative searches from the CMS collaboration are used to demonstrate the validity of the simplified likelihood approach under realistic conditions.

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....

On maximal surfaces in asymptotically flat space-times

International Nuclear Information System (INIS)

Bartnik, R.; Chrusciel, P.T.; O Murchadha, N.

1990-01-01

Existence of maximal and 'almost maximal' hypersurfaces in asymptotically flat space-times is established under boundary conditions weaker than those considered previously. We show in particular that every vacuum evolution of asymptotically flat data for Einstein equations can be foliated by slices maximal outside a spatially compact set and that every (strictly) stationary asymptotically flat space-time can be foliated by maximal hypersurfaces. Amongst other uniqueness results, we show that maximal hypersurface can be used to 'partially fix' an asymptotic Poincare group. (orig.)

Maximize x(a - x)

Science.gov (United States)

Lange, L. H.

1974-01-01

Five different methods for determining the maximizing condition for x(a - x) are presented. Included is the ancient Greek version and a method attributed to Fermat. None of the proofs use calculus. (LS)

Power-law inter-spike interval distributions infer a conditional maximization of entropy in cortical neurons.

Directory of Open Access Journals (Sweden)

Yasuhiro Tsubo

Full Text Available The brain is considered to use a relatively small amount of energy for its efficient information processing. Under a severe restriction on the energy consumption, the maximization of mutual information (MMI, which is adequate for designing artificial processing machines, may not suit for the brain. The MMI attempts to send information as accurate as possible and this usually requires a sufficient energy supply for establishing clearly discretized communication bands. Here, we derive an alternative hypothesis for neural code from the neuronal activities recorded juxtacellularly in the sensorimotor cortex of behaving rats. Our hypothesis states that in vivo cortical neurons maximize the entropy of neuronal firing under two constraints, one limiting the energy consumption (as assumed previously and one restricting the uncertainty in output spike sequences at given firing rate. Thus, the conditional maximization of firing-rate entropy (CMFE solves a tradeoff between the energy cost and noise in neuronal response. In short, the CMFE sends a rich variety of information through broader communication bands (i.e., widely distributed firing rates at the cost of accuracy. We demonstrate that the CMFE is reflected in the long-tailed, typically power law, distributions of inter-spike intervals obtained for the majority of recorded neurons. In other words, the power-law tails are more consistent with the CMFE rather than the MMI. Thus, we propose the mathematical principle by which cortical neurons may represent information about synaptic input into their output spike trains.

Evaluation of tomographic image quality of extended and conventional parallel hole collimators using maximum likelihood expectation maximization algorithm by Monte Carlo simulations.

Science.gov (United States)

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.

a Threshold-Free Filtering Algorithm for Airborne LIDAR Point Clouds Based on Expectation-Maximization

Science.gov (United States)

Hui, Z.; Cheng, P.; Ziggah, Y. Y.; Nie, Y.

2018-04-01

Filtering is a key step for most applications of airborne LiDAR point clouds. Although lots of filtering algorithms have been put forward in recent years, most of them suffer from parameters setting or thresholds adjusting, which will be time-consuming and reduce the degree of automation of the algorithm. To overcome this problem, this paper proposed a threshold-free filtering algorithm based on expectation-maximization. The proposed algorithm is developed based on an assumption that point clouds are seen as a mixture of Gaussian models. The separation of ground points and non-ground points from point clouds can be replaced as a separation of a mixed Gaussian model. Expectation-maximization (EM) is applied for realizing the separation. EM is used to calculate maximum likelihood estimates of the mixture parameters. Using the estimated parameters, the likelihoods of each point belonging to ground or object can be computed. After several iterations, point clouds can be labelled as the component with a larger likelihood. Furthermore, intensity information was also utilized to optimize the filtering results acquired using the EM method. The proposed algorithm was tested using two different datasets used in practice. Experimental results showed that the proposed method can filter non-ground points effectively. To quantitatively evaluate the proposed method, this paper adopted the dataset provided by the ISPRS for the test. The proposed algorithm can obtain a 4.48 % total error which is much lower than most of the eight classical filtering algorithms reported by the ISPRS.

Fingermark evidence evaluation based on automated fingerprint identification system matching scores: the effect of different types of conditioning on likelihood ratios.

Science.gov (United States)

Alberink, Ivo; de Jongh, Arent; Rodriguez, Crystal

2014-01-01

In recent studies, the evidential value of the similarity of minutiae configurations of fingermarks and fingerprints, for example expressed by automated fingerprint identification systems (AFIS), is determined by likelihood ratios (LRs). The paper explores whether there is an effect on LRs if conditioning takes place on specified fingers, fingerprints, or fingermarks under competing hypotheses: In addition, an approach is explored where conditioning is asymmetric. Comparisons between fingerprints and simulated fingermarks with eight minutiae are performed to produce similarity score distributions for each type of conditioning, given a fixed AFIS matching algorithm. Both similarity scores and LRs are significantly different if the conditioning changes. Given a common-source scenario, "LRs" resulting from asymmetric conditioning are on average higher. The difference may reach a factor of 2000. As conditioning on a suspect's finger(print) is labor-intensive and requires a cooperating suspect, it is recommended to just condition on the number of minutiae in the fingermark. © 2013 American Academy of Forensic Sciences.

The phylogenetic likelihood library.

Science.gov (United States)

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.

Maximal Inequalities for Dependent Random Variables

DEFF Research Database (Denmark)

Hoffmann-Jorgensen, Jorgen

2016-01-01

Maximal inequalities play a crucial role in many probabilistic limit theorem; for instance, the law of large numbers, the law of the iterated logarithm, the martingale limit theorem and the central limit theorem. Let X-1, X-2,... be random variables with partial sums S-k = X-1 + ... + X-k. Then a......Maximal inequalities play a crucial role in many probabilistic limit theorem; for instance, the law of large numbers, the law of the iterated logarithm, the martingale limit theorem and the central limit theorem. Let X-1, X-2,... be random variables with partial sums S-k = X-1 + ... + X......-k. Then a maximal inequality gives conditions ensuring that the maximal partial sum M-n = max(1) (...

Tri-maximal vs. bi-maximal neutrino mixing

International Nuclear Information System (INIS)

Scott, W.G

2000-01-01

It is argued that data from atmospheric and solar neutrino experiments point strongly to tri-maximal or bi-maximal lepton mixing. While ('optimised') bi-maximal mixing gives an excellent a posteriori fit to the data, tri-maximal mixing is an a priori hypothesis, which is not excluded, taking account of terrestrial matter effects

Higher dimensional maximally symmetric stationary manifold with pure gauge condition and codimension one flat submanifold

International Nuclear Information System (INIS)

Wiliardy, Abednego; Gunara, Bobby Eka

2016-01-01

An n dimensional flat manifold N is embedded into an n +1 dimensional stationary manifold M. The metric of M is derived from a general form of stationary manifold. By taking several assumption, such as 1) the ambient manifold M to be maximally symmetric space and satisfying a pure gauge condition, and 2) the submanifold is taken to be flat, then we find the solution that satisfies Ricci scalar of N . Moreover, we determine whether the solution is compatible with the Ricci and Riemann tensor of manifold N depending on the dimension. (paper)

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

Marginal likelihood estimation of negative binomial parameters with applications to RNA-seq data.

Science.gov (United States)

León-Novelo, Luis; Fuentes, Claudio; Emerson, Sarah

2017-10-01

RNA-Seq data characteristically exhibits large variances, which need to be appropriately accounted for in any proposed model. We first explore the effects of this variability on the maximum likelihood estimator (MLE) of the dispersion parameter of the negative binomial distribution, and propose instead to use an estimator obtained via maximization of the marginal likelihood in a conjugate Bayesian framework. We show, via simulation studies, that the marginal MLE can better control this variation and produce a more stable and reliable estimator. We then formulate a conjugate Bayesian hierarchical model, and use this new estimator to propose a Bayesian hypothesis test to detect differentially expressed genes in RNA-Seq data. We use numerical studies to show that our much simpler approach is competitive with other negative binomial based procedures, and we use a real data set to illustrate the implementation and flexibility of the procedure. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

HLIBCov: Parallel Hierarchical Matrix Approximation of Large Covariance Matrices and Likelihoods with Applications in Parameter Identification

KAUST Repository

Litvinenko, Alexander

2017-09-26

The main goal of this article is to introduce the parallel hierarchical matrix library HLIBpro to the statistical community. We describe the HLIBCov package, which is an extension of the HLIBpro library for approximating large covariance matrices and maximizing likelihood functions. We show that an approximate Cholesky factorization of a dense matrix of size $2M\\\\times 2M$ can be computed on a modern multi-core desktop in few minutes. Further, HLIBCov is used for estimating the unknown parameters such as the covariance length, variance and smoothness parameter of a Mat\\\\\\'ern covariance function by maximizing the joint Gaussian log-likelihood function. The computational bottleneck here is expensive linear algebra arithmetics due to large and dense covariance matrices. Therefore covariance matrices are approximated in the hierarchical ($\\\\H$-) matrix format with computational cost $\\\\mathcal{O}(k^2n \\\\log^2 n/p)$ and storage $\\\\mathcal{O}(kn \\\\log n)$, where the rank $k$ is a small integer (typically $k<25$), $p$ the number of cores and $n$ the number of locations on a fairly general mesh. We demonstrate a synthetic example, where the true values of known parameters are known. For reproducibility we provide the C++ code, the documentation, and the synthetic data.

HLIBCov: Parallel Hierarchical Matrix Approximation of Large Covariance Matrices and Likelihoods with Applications in Parameter Identification

KAUST Repository

Litvinenko, Alexander

2017-09-24

The main goal of this article is to introduce the parallel hierarchical matrix library HLIBpro to the statistical community. We describe the HLIBCov package, which is an extension of the HLIBpro library for approximating large covariance matrices and maximizing likelihood functions. We show that an approximate Cholesky factorization of a dense matrix of size $2M\\\\times 2M$ can be computed on a modern multi-core desktop in few minutes. Further, HLIBCov is used for estimating the unknown parameters such as the covariance length, variance and smoothness parameter of a Mat\\\\\\'ern covariance function by maximizing the joint Gaussian log-likelihood function. The computational bottleneck here is expensive linear algebra arithmetics due to large and dense covariance matrices. Therefore covariance matrices are approximated in the hierarchical ($\\\\mathcal{H}$-) matrix format with computational cost $\\\\mathcal{O}(k^2n \\\\log^2 n/p)$ and storage $\\\\mathcal{O}(kn \\\\log n)$, where the rank $k$ is a small integer (typically $k<25$), $p$ the number of cores and $n$ the number of locations on a fairly general mesh. We demonstrate a synthetic example, where the true values of known parameters are known. For reproducibility we provide the C++ code, the documentation, and the synthetic data.

Empirical Likelihood in Nonignorable Covariate-Missing Data Problems.

Science.gov (United States)

Xie, Yanmei; Zhang, Biao

2017-04-20

Missing covariate data occurs often in regression analysis, which frequently arises in the health and social sciences as well as in survey sampling. We study methods for the analysis of a nonignorable covariate-missing data problem in an assumed conditional mean function when some covariates are completely observed but other covariates are missing for some subjects. We adopt the semiparametric perspective of Bartlett et al. (Improving upon the efficiency of complete case analysis when covariates are MNAR. Biostatistics 2014;15:719-30) on regression analyses with nonignorable missing covariates, in which they have introduced the use of two working models, the working probability model of missingness and the working conditional score model. In this paper, we study an empirical likelihood approach to nonignorable covariate-missing data problems with the objective of effectively utilizing the two working models in the analysis of covariate-missing data. We propose a unified approach to constructing a system of unbiased estimating equations, where there are more equations than unknown parameters of interest. One useful feature of these unbiased estimating equations is that they naturally incorporate the incomplete data into the data analysis, making it possible to seek efficient estimation of the parameter of interest even when the working regression function is not specified to be the optimal regression function. We apply the general methodology of empirical likelihood to optimally combine these unbiased estimating equations. We propose three maximum empirical likelihood estimators of the underlying regression parameters and compare their efficiencies with other existing competitors. We present a simulation study to compare the finite-sample performance of various methods with respect to bias, efficiency, and robustness to model misspecification. The proposed empirical likelihood method is also illustrated by an analysis of a data set from the US National Health and

Logic of likelihood

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

Evaluating Fast Maximum Likelihood-Based Phylogenetic Programs Using Empirical Phylogenomic Data Sets

Science.gov (United States)

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

Gradient Dynamics and Entropy Production Maximization

Science.gov (United States)

Janečka, Adam; Pavelka, Michal

2018-01-01

We compare two methods for modeling dissipative processes, namely gradient dynamics and entropy production maximization. Both methods require similar physical inputs-how energy (or entropy) is stored and how it is dissipated. Gradient dynamics describes irreversible evolution by means of dissipation potential and entropy, it automatically satisfies Onsager reciprocal relations as well as their nonlinear generalization (Maxwell-Onsager relations), and it has statistical interpretation. Entropy production maximization is based on knowledge of free energy (or another thermodynamic potential) and entropy production. It also leads to the linear Onsager reciprocal relations and it has proven successful in thermodynamics of complex materials. Both methods are thermodynamically sound as they ensure approach to equilibrium, and we compare them and discuss their advantages and shortcomings. In particular, conditions under which the two approaches coincide and are capable of providing the same constitutive relations are identified. Besides, a commonly used but not often mentioned step in the entropy production maximization is pinpointed and the condition of incompressibility is incorporated into gradient dynamics.

Corporate Social Responsibility and Profit Maximizing Behaviour

OpenAIRE

Becchetti, Leonardo; Giallonardo, Luisa; Tessitore, Maria Elisabetta

2005-01-01

We examine the behavior of a profit maximizing monopolist in a horizontal differentiation model in which consumers differ in their degree of social responsibility (SR) and consumers SR is dynamically influenced by habit persistence. The model outlines parametric conditions under which (consumer driven) corporate social responsibility is an optimal choice compatible with profit maximizing behavior.

Maximum Likelihood DOA Estimation of Multiple Wideband Sources in the Presence of Nonuniform Sensor Noise

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 Cramér-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.

Self-consistent collective-coordinate method for ''maximally-decoupled'' collective subspace and its boson mapping: Quantum theory of ''maximally-decoupled'' collective motion

International Nuclear Information System (INIS)

Marumori, T.; Sakata, F.; Maskawa, T.; Une, T.; Hashimoto, Y.

1983-01-01

The main purpose of this paper is to develop a full quantum theory, which is capable by itself of determining a ''maximally-decoupled'' collective motion. The paper is divided into two parts. In the first part, the motivation and basic idea of the theory are explained, and the ''maximal-decoupling condition'' on the collective motion is formulated within the framework of the time-dependent Hartree-Fock theory, in a general form called the invariance principle of the (time-dependent) Schrodinger equation. In the second part, it is shown that when the author positively utilize the invariance principle, we can construct a full quantum theory of the ''maximally-decoupled'' collective motion. This quantum theory is shown to be a generalization of the kinematical boson-mapping theories so far developed, in such a way that the dynamical ''maximal-decoupling condition'' on the collective motion is automatically satisfied

Dissociating response conflict and error likelihood in anterior cingulate cortex.

Science.gov (United States)

Yeung, Nick; Nieuwenhuis, Sander

2009-11-18

Neuroimaging studies consistently report activity in anterior cingulate cortex (ACC) in conditions of high cognitive demand, leading to the view that ACC plays a crucial role in the control of cognitive processes. According to one prominent theory, the sensitivity of ACC to task difficulty reflects its role in monitoring for the occurrence of competition, or "conflict," between responses to signal the need for increased cognitive control. However, a contrasting theory proposes that ACC is the recipient rather than source of monitoring signals, and that ACC activity observed in relation to task demand reflects the role of this region in learning about the likelihood of errors. Response conflict and error likelihood are typically confounded, making the theories difficult to distinguish empirically. The present research therefore used detailed computational simulations to derive contrasting predictions regarding ACC activity and error rate as a function of response speed. The simulations demonstrated a clear dissociation between conflict and error likelihood: fast response trials are associated with low conflict but high error likelihood, whereas slow response trials show the opposite pattern. Using the N2 component as an index of ACC activity, an EEG study demonstrated that when conflict and error likelihood are dissociated in this way, ACC activity tracks conflict and is negatively correlated with error likelihood. These findings support the conflict-monitoring theory and suggest that, in speeded decision tasks, ACC activity reflects current task demands rather than the retrospective coding of past performance.

Organizational Justice and Men's Likelihood to Sexually Harass: The Moderating Role of Sexism and Personality

Science.gov (United States)

Krings, Franciska; Facchin, Stephanie

2009-01-01

This study demonstrated relations between men's perceptions of organizational justice and increased sexual harassment proclivities. Respondents reported higher likelihood to sexually harass under conditions of low interactional justice, suggesting that sexual harassment likelihood may increase as a response to perceived injustice. Moreover, the…

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

Gaussian copula as a likelihood function for environmental models

Science.gov (United States)

Wani, O.; Espadas, G.; Cecinati, F.; Rieckermann, J.

2017-12-01

Parameter estimation of environmental models always comes with uncertainty. To formally quantify this parametric uncertainty, a likelihood function needs to be formulated, which is defined as the probability of observations given fixed values of the parameter set. A likelihood function allows us to infer parameter values from observations using Bayes' theorem. The challenge is to formulate a likelihood function that reliably describes the error generating processes which lead to the observed monitoring data, such as rainfall and runoff. If the likelihood function is not representative of the error statistics, the parameter inference will give biased parameter values. Several uncertainty estimation methods that are currently being used employ Gaussian processes as a likelihood function, because of their favourable analytical properties. Box-Cox transformation is suggested to deal with non-symmetric and heteroscedastic errors e.g. for flow data which are typically more uncertain in high flows than in periods with low flows. Problem with transformations is that the results are conditional on hyper-parameters, for which it is difficult to formulate the analyst's belief a priori. In an attempt to address this problem, in this research work we suggest learning the nature of the error distribution from the errors made by the model in the "past" forecasts. We use a Gaussian copula to generate semiparametric error distributions . 1) We show that this copula can be then used as a likelihood function to infer parameters, breaking away from the practice of using multivariate normal distributions. Based on the results from a didactical example of predicting rainfall runoff, 2) we demonstrate that the copula captures the predictive uncertainty of the model. 3) Finally, we find that the properties of autocorrelation and heteroscedasticity of errors are captured well by the copula, eliminating the need to use transforms. In summary, our findings suggest that copulas are an

Developing maximal neuromuscular power: part 2 - training considerations for improving maximal power production.

Science.gov (United States)

Cormie, Prue; McGuigan, Michael R; Newton, Robert U

2011-02-01

/or weightlifting exercises performed with loads ranging from 50% to 90% of 1RM appears to be the most potent loading stimulus for improving maximal power in complex movements. Furthermore, plyometric exercises should involve stretch rates as well as stretch loads that are similar to those encountered in each specific sport and involve little to no external resistance. These loading conditions allow for superior transfer to performance because they require similar movement velocities to those typically encountered in sport. Third, it is vital to consider the individual athlete's window of adaptation (i.e. the magnitude of potential for improvement) for each neuromuscular factor contributing to maximal power production when developing an effective and efficient power training programme. A training programme that focuses on the least developed factor contributing to maximal power will prompt the greatest neuromuscular adaptations and therefore result in superior performance improvements for that individual. Finally, a key consideration for the long-term development of an athlete's maximal power production capacity is the need for an integration of numerous power training techniques. This integration allows for variation within power meso-/micro-cycles while still maintaining specificity, which is theorized to lead to the greatest long-term improvement in maximal power.

An efficient forward-reverse expectation-maximization algorithm for statistical inference in stochastic reaction networks

KAUST Repository

Vilanova, Pedro

2016-01-07

In this work, we present an extension of the forward-reverse representation introduced in Simulation of forward-reverse stochastic representations for conditional diffusions , a 2014 paper by Bayer and Schoenmakers to the context of stochastic reaction networks (SRNs). We apply this stochastic representation to the computation of efficient approximations of expected values of functionals of SRN bridges, i.e., SRNs conditional on their values in the extremes of given time-intervals. We then employ this SRN bridge-generation technique to the statistical inference problem of approximating reaction propensities based on discretely observed data. To this end, we introduce a two-phase iterative inference method in which, during phase I, we solve a set of deterministic optimization problems where the SRNs are replaced by their reaction-rate ordinary differential equations approximation; then, during phase II, we apply the Monte Carlo version of the Expectation-Maximization algorithm to the phase I output. By selecting a set of over-dispersed seeds as initial points in phase I, the output of parallel runs from our two-phase method is a cluster of approximate maximum likelihood estimates. Our results are supported by numerical examples.

Phenomenology of maximal and near-maximal lepton mixing

International Nuclear Information System (INIS)

Gonzalez-Garcia, M. C.; Pena-Garay, Carlos; Nir, Yosef; Smirnov, Alexei Yu.

2001-01-01

The possible existence of maximal or near-maximal lepton mixing constitutes an intriguing challenge for fundamental theories of flavor. We study the phenomenological consequences of maximal and near-maximal mixing of the electron neutrino with other (x=tau and/or muon) neutrinos. We describe the deviations from maximal mixing in terms of a parameter ε(equivalent to)1-2sin 2 θ ex and quantify the present experimental status for |ε| e mixing comes from solar neutrino experiments. We find that the global analysis of solar neutrino data allows maximal mixing with confidence level better than 99% for 10 -8 eV 2 ∼ 2 ∼ -7 eV 2 . In the mass ranges Δm 2 ∼>1.5x10 -5 eV 2 and 4x10 -10 eV 2 ∼ 2 ∼ -7 eV 2 the full interval |ε| e mixing in atmospheric neutrinos, supernova neutrinos, and neutrinoless double beta decay

Insecticide resistance, control failure likelihood and the First Law of Geography.

Science.gov (United States)

Guedes, Raul Narciso C

2017-03-01

Insecticide resistance is a broadly recognized ecological backlash resulting from insecticide use and is widely reported among arthropod pest species with well-recognized underlying mechanisms and consequences. Nonetheless, insecticide resistance is the subject of evolving conceptual views that introduces a different concept useful if recognized in its own right - the risk or likelihood of control failure. Here we suggest an experimental approach to assess the likelihood of control failure of an insecticide allowing for consistent decision-making regarding management of insecticide resistance. We also challenge the current emphasis on limited spatial sampling of arthropod populations for resistance diagnosis in favor of comprehensive spatial sampling. This necessarily requires larger population sampling - aiming to use spatial analysis in area-wide surveys - to recognize focal points of insecticide resistance and/or control failure that will better direct management efforts. The continuous geographical scale of such surveys will depend on the arthropod pest species, the pattern of insecticide use and many other potential factors. Regardless, distance dependence among sampling sites should still hold, following the maxim that the closer two things are, the more they resemble each other, which is the basis of Tobler's First Law of Geography. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

Likelihood Approximation With Hierarchical Matrices For Large Spatial Datasets

KAUST Repository

Litvinenko, Alexander

2017-09-03

We use available measurements to estimate the unknown parameters (variance, smoothness parameter, and covariance length) of a covariance function by maximizing the joint Gaussian log-likelihood function. To overcome cubic complexity in the linear algebra, we approximate the discretized covariance function in the hierarchical (H-) matrix format. The H-matrix format has a log-linear computational cost and storage O(kn log n), where the rank k is a small integer and n is the number of locations. The H-matrix technique allows us to work with general covariance matrices in an efficient way, since H-matrices can approximate inhomogeneous covariance functions, with a fairly general mesh that is not necessarily axes-parallel, and neither the covariance matrix itself nor its inverse have to be sparse. We demonstrate our method with Monte Carlo simulations and an application to soil moisture data. The C, C++ codes and data are freely available.

Bayesian interpretation of Generalized empirical likelihood by maximum entropy

OpenAIRE

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...

A retrospective likelihood approach for efficient integration of multiple omics factors in case-control association studies.

Science.gov (United States)

Balliu, Brunilda; Tsonaka, Roula; Boehringer, Stefan; Houwing-Duistermaat, Jeanine

2015-03-01

Integrative omics, the joint analysis of outcome and multiple types of omics data, such as genomics, epigenomics, and transcriptomics data, constitute a promising approach for powerful and biologically relevant association studies. These studies often employ a case-control design, and often include nonomics covariates, such as age and gender, that may modify the underlying omics risk factors. An open question is how to best integrate multiple omics and nonomics information to maximize statistical power in case-control studies that ascertain individuals based on the phenotype. Recent work on integrative omics have used prospective approaches, modeling case-control status conditional on omics, and nonomics risk factors. Compared to univariate approaches, jointly analyzing multiple risk factors with a prospective approach increases power in nonascertained cohorts. However, these prospective approaches often lose power in case-control studies. In this article, we propose a novel statistical method for integrating multiple omics and nonomics factors in case-control association studies. Our method is based on a retrospective likelihood function that models the joint distribution of omics and nonomics factors conditional on case-control status. The new method provides accurate control of Type I error rate and has increased efficiency over prospective approaches in both simulated and real data. © 2015 Wiley Periodicals, Inc.

Improved Expectation Maximization Algorithm for Gaussian Mixed Model Using the Kernel Method

Directory of Open Access Journals (Sweden)

Mohd Izhan Mohd Yusoff

2013-01-01

Full Text Available Fraud activities have contributed to heavy losses suffered by telecommunication companies. In this paper, we attempt to use Gaussian mixed model, which is a probabilistic model normally used in speech recognition to identify fraud calls in the telecommunication industry. We look at several issues encountered when calculating the maximum likelihood estimates of the Gaussian mixed model using an Expectation Maximization algorithm. Firstly, we look at a mechanism for the determination of the initial number of Gaussian components and the choice of the initial values of the algorithm using the kernel method. We show via simulation that the technique improves the performance of the algorithm. Secondly, we developed a procedure for determining the order of the Gaussian mixed model using the log-likelihood function and the Akaike information criteria. Finally, for illustration, we apply the improved algorithm to real telecommunication data. The modified method will pave the way to introduce a comprehensive method for detecting fraud calls in future work.

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...

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

Likelihood devices in spatial statistics

NARCIS (Netherlands)

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

Maximal Bell's inequality violation for non-maximal entanglement

International Nuclear Information System (INIS)

Kobayashi, M.; Khanna, F.; Mann, A.; Revzen, M.; Santana, A.

2004-01-01

Bell's inequality violation (BIQV) for correlations of polarization is studied for a product state of two two-mode squeezed vacuum (TMSV) states. The violation allowed is shown to attain its maximal limit for all values of the squeezing parameter, ζ. We show via an explicit example that a state whose entanglement is not maximal allow maximal BIQV. The Wigner function of the state is non-negative and the average value of either polarization is nil

Half-maximal supersymmetry from exceptional field theory

Energy Technology Data Exchange (ETDEWEB)

Malek, Emanuel [Arnold Sommerfeld Center for Theoretical Physics, Department fuer Physik, Ludwig-Maximilians-Universitaet Muenchen (Germany)

2017-10-15

We study D ≥ 4-dimensional half-maximal flux backgrounds using exceptional field theory. We define the relevant generalised structures and also find the integrability conditions which give warped half-maximal Minkowski{sub D} and AdS{sub D} vacua. We then show how to obtain consistent truncations of type II / 11-dimensional SUGRA which break half the supersymmetry. Such truncations can be defined on backgrounds admitting exceptional generalised SO(d - 1 - N) structures, where d = 11 - D, and N is the number of vector multiplets obtained in the lower-dimensional theory. Our procedure yields the most general embedding tensors satisfying the linear constraint of half-maximal gauged SUGRA. We use this to prove that all D ≥ 4 half-maximal warped AdS{sub D} and Minkowski{sub D} vacua of type II / 11-dimensional SUGRA admit a consistent truncation keeping only the gravitational supermultiplet. We also show to obtain heterotic double field theory from exceptional field theory and comment on the M-theory / heterotic duality. In five dimensions, we find a new SO(5, N) double field theory with a (6 + N)-dimensional extended space. Its section condition has one solution corresponding to 10-dimensional N = 1 supergravity and another yielding six-dimensional N = (2, 0) SUGRA. (copyright 2017 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)

Efficient Maximum Likelihood Estimation for Pedigree Data with the Sum-Product Algorithm.

Science.gov (United States)

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.

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)

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...

Conditional maximum-entropy method for selecting prior distributions in Bayesian statistics

Science.gov (United States)

Abe, Sumiyoshi

2014-11-01

The conditional maximum-entropy method (abbreviated here as C-MaxEnt) is formulated for selecting prior probability distributions in Bayesian statistics for parameter estimation. This method is inspired by a statistical-mechanical approach to systems governed by dynamics with largely separated time scales and is based on three key concepts: conjugate pairs of variables, dimensionless integration measures with coarse-graining factors and partial maximization of the joint entropy. The method enables one to calculate a prior purely from a likelihood in a simple way. It is shown, in particular, how it not only yields Jeffreys's rules but also reveals new structures hidden behind them.

Maximizing and customer loyalty: Are maximizers less loyal?

Directory of Open Access Journals (Sweden)

Linda Lai

2011-06-01

Full Text Available Despite their efforts to choose the best of all available solutions, maximizers seem to be more inclined than satisficers to regret their choices and to experience post-decisional dissonance. Maximizers may therefore be expected to change their decisions more frequently and hence exhibit lower customer loyalty to providers of products and services compared to satisficers. Findings from the study reported here (N = 1978 support this prediction. Maximizers reported significantly higher intentions to switch to another service provider (television provider than satisficers. Maximizers' intentions to switch appear to be intensified and mediated by higher proneness to regret, increased desire to discuss relevant choices with others, higher levels of perceived knowledge of alternatives, and higher ego involvement in the end product, compared to satisficers. Opportunities for future research are suggested.

Trend analysis of the power law process using Expectation-Maximization algorithm for data censored by inspection intervals

International Nuclear Information System (INIS)

Taghipour, Sharareh; Banjevic, Dragan

2011-01-01

Trend analysis is a common statistical method used to investigate the operation and changes of a repairable system over time. This method takes historical failure data of a system or a group of similar systems and determines whether the recurrent failures exhibit an increasing or decreasing trend. Most trend analysis methods proposed in the literature assume that the failure times are known, so the failure data is statistically complete; however, in many situations, such as hidden failures, failure times are subject to censoring. In this paper we assume that the failure process of a group of similar independent repairable units follows a non-homogenous Poisson process with a power law intensity function. Moreover, the failure data are subject to left, interval and right censoring. The paper proposes using the likelihood ratio test to check for trends in the failure data. It uses the Expectation-Maximization (EM) algorithm to find the parameters, which maximize the data likelihood in the case of null and alternative hypotheses. A recursive procedure is used to solve the main technical problem of calculating the expected values in the Expectation step. The proposed method is applied to a hospital's maintenance data for trend analysis of the components of a general infusion pump.

Optimized Large-scale CMB Likelihood and Quadratic Maximum Likelihood Power Spectrum Estimation

Science.gov (United States)

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.

Deformation of log-likelihood loss function for multiclass boosting.

Science.gov (United States)

Kanamori, Takafumi

2010-09-01

The purpose of this paper is to study loss functions in multiclass classification. In classification problems, the decision function is estimated by minimizing an empirical loss function, and then, the output label is predicted by using the estimated decision function. We propose a class of loss functions which is obtained by a deformation of the log-likelihood loss function. There are four main reasons why we focus on the deformed log-likelihood loss function: (1) this is a class of loss functions which has not been deeply investigated so far, (2) in terms of computation, a boosting algorithm with a pseudo-loss is available to minimize the proposed loss function, (3) the proposed loss functions provide a clear correspondence between the decision functions and conditional probabilities of output labels, (4) the proposed loss functions satisfy the statistical consistency of the classification error rate which is a desirable property in classification problems. Based on (3), we show that the deformed log-likelihood loss provides a model of mislabeling which is useful as a statistical model of medical diagnostics. We also propose a robust loss function against outliers in multiclass classification based on our approach. The robust loss function is a natural extension of the existing robust loss function for binary classification. A model of mislabeling and a robust loss function are useful to cope with noisy data. Some numerical studies are presented to show the robustness of the proposed loss function. A mathematical characterization of the deformed log-likelihood loss function is also presented. Copyright 2010 Elsevier Ltd. All rights reserved.

Essays on empirical likelihood in economics

NARCIS (Netherlands)

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.

Composite likelihood estimation of demographic parameters

Directory of Open Access Journals (Sweden)

Garrigan Daniel

2009-11-01

Full Text Available Abstract Background Most existing likelihood-based methods for fitting historical demographic models to DNA sequence polymorphism data to do not scale feasibly up to the level of whole-genome data sets. Computational economies can be achieved by incorporating two forms of pseudo-likelihood: composite and approximate likelihood methods. Composite likelihood enables scaling up to large data sets because it takes the product of marginal likelihoods as an estimator of the likelihood of the complete data set. This approach is especially useful when a large number of genomic regions constitutes the data set. Additionally, approximate likelihood methods can reduce the dimensionality of the data by summarizing the information in the original data by either a sufficient statistic, or a set of statistics. Both composite and approximate likelihood methods hold promise for analyzing large data sets or for use in situations where the underlying demographic model is complex and has many parameters. This paper considers a simple demographic model of allopatric divergence between two populations, in which one of the population is hypothesized to have experienced a founder event, or population bottleneck. A large resequencing data set from human populations is summarized by the joint frequency spectrum, which is a matrix of the genomic frequency spectrum of derived base frequencies in two populations. A Bayesian Metropolis-coupled Markov chain Monte Carlo (MCMCMC method for parameter estimation is developed that uses both composite and likelihood methods and is applied to the three different pairwise combinations of the human population resequence data. The accuracy of the method is also tested on data sets sampled from a simulated population model with known parameters. Results The Bayesian MCMCMC method also estimates the ratio of effective population size for the X chromosome versus that of the autosomes. The method is shown to estimate, with reasonable

Maximally flat radiation patterns of a circular aperture

Science.gov (United States)

Minkovich, B. M.; Mints, M. Ia.

1989-08-01

The paper presents an explicit solution to the problems of maximizing the area utilization coefficient and of obtaining the best approximation (on the average) of a sectorial Pi-shaped radiation pattern of an antenna with a circular aperture when Butterworth conditions are imposed on the approximating pattern with the aim of flattening it. Constraints on the choice of admissible minimum and maximum antenna dimensions are determined which make possible the synthesis of maximally flat patterns with small sidelobes.

A composite likelihood approach for spatially correlated survival data

Science.gov (United States)

Paik, Jane; Ying, Zhiliang

2013-01-01

The aim of this paper is to provide a composite likelihood approach to handle spatially correlated survival data using pairwise joint distributions. With e-commerce data, a recent question of interest in marketing research has been to describe spatially clustered purchasing behavior and to assess whether geographic distance is the appropriate metric to describe purchasing dependence. We present a model for the dependence structure of time-to-event data subject to spatial dependence to characterize purchasing behavior from the motivating example from e-commerce data. We assume the Farlie-Gumbel-Morgenstern (FGM) distribution and then model the dependence parameter as a function of geographic and demographic pairwise distances. For estimation of the dependence parameters, we present pairwise composite likelihood equations. We prove that the resulting estimators exhibit key properties of consistency and asymptotic normality under certain regularity conditions in the increasing-domain framework of spatial asymptotic theory. PMID:24223450

A composite likelihood approach for spatially correlated survival data.

Science.gov (United States)

Paik, Jane; Ying, Zhiliang

2013-01-01

The aim of this paper is to provide a composite likelihood approach to handle spatially correlated survival data using pairwise joint distributions. With e-commerce data, a recent question of interest in marketing research has been to describe spatially clustered purchasing behavior and to assess whether geographic distance is the appropriate metric to describe purchasing dependence. We present a model for the dependence structure of time-to-event data subject to spatial dependence to characterize purchasing behavior from the motivating example from e-commerce data. We assume the Farlie-Gumbel-Morgenstern (FGM) distribution and then model the dependence parameter as a function of geographic and demographic pairwise distances. For estimation of the dependence parameters, we present pairwise composite likelihood equations. We prove that the resulting estimators exhibit key properties of consistency and asymptotic normality under certain regularity conditions in the increasing-domain framework of spatial asymptotic theory.

Principles of maximally classical and maximally realistic quantum ...

Indian Academy of Sciences (India)

Principles of maximally classical and maximally realistic quantum mechanics. S M ROY. Tata Institute of Fundamental Research, Homi Bhabha Road, Mumbai 400 005, India. Abstract. Recently Auberson, Mahoux, Roy and Singh have proved a long standing conjecture of Roy and Singh: In 2N-dimensional phase space, ...

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.

Profit maximization mitigates competition

DEFF Research Database (Denmark)

Dierker, Egbert; Grodal, Birgit

1996-01-01

We consider oligopolistic markets in which the notion of shareholders' utility is well-defined and compare the Bertrand-Nash equilibria in case of utility maximization with those under the usual profit maximization hypothesis. Our main result states that profit maximization leads to less price...... competition than utility maximization. Since profit maximization tends to raise prices, it may be regarded as beneficial for the owners as a whole. Moreover, if profit maximization is a good proxy for utility maximization, then there is no need for a general equilibrium analysis that takes the distribution...... of profits among consumers fully into account and partial equilibrium analysis suffices...

On Maximal Non-Disjoint Families of Subsets

Directory of Open Access Journals (Sweden)

Yu. A. Zuev

2017-01-01

Full Text Available The paper studies maximal non-disjoint families of subsets of a finite set. Non-disjointness means that any two subsets of a family have a nonempty intersection. The maximality is expressed by the fact that adding a new subset to the family cannot increase its power without violating a non-disjointness condition. Studying the properties of such families is an important section of the extreme theory of sets. Along with purely combinatorial interest, the problems considered here play an important role in informatics, anti-noise coding, and cryptography.In 1961 this problem saw the light of day in the Erdos, Ko and Rado paper, which established a maximum power of the non-disjoint family of subsets of equal power. In 1974 the Erdos and Claytman publication estimated the number of maximal non-disjoint families of subsets without involving the equality of their power. These authors failed to establish an asymptotics of the logarithm of the number of such families when the power of a basic finite set tends to infinity. However, they suggested such an asymptotics as a hypothesis. A.D. Korshunov in two publications in 2003 and 2005 established the asymptotics for the number of non-disjoint families of the subsets of arbitrary powers without maximality condition of these families.The basis for the approach used in the paper to study the families of subsets is their description in the language of Boolean functions. A one-to-one correspondence between a family of subsets and a Boolean function is established by the fact that the characteristic vectors of subsets of a family are considered to be the unit sets of a Boolean function. The main theoretical result of the paper is that the maximal non-disjoint families are in one-to-one correspondence with the monotonic self-dual Boolean functions. When estimating the number of maximal non-disjoint families, this allowed us to use the result of A.A. Sapozhenko, who established the asymptotics of the number of the

AUC-Maximized Deep Convolutional Neural Fields for Protein Sequence Labeling.

Science.gov (United States)

Wang, Sheng; Sun, Siqi; Xu, Jinbo

2016-09-01

Deep Convolutional Neural Networks (DCNN) has shown excellent performance in a variety of machine learning tasks. This paper presents Deep Convolutional Neural Fields (DeepCNF), an integration of DCNN with Conditional Random Field (CRF), for sequence labeling with an imbalanced label distribution. The widely-used training methods, such as maximum-likelihood and maximum labelwise accuracy, do not work well on imbalanced data. To handle this, we present a new training algorithm called maximum-AUC for DeepCNF. That is, we train DeepCNF by directly maximizing the empirical Area Under the ROC Curve (AUC), which is an unbiased measurement for imbalanced data. To fulfill this, we formulate AUC in a pairwise ranking framework, approximate it by a polynomial function and then apply a gradient-based procedure to optimize it. Our experimental results confirm that maximum-AUC greatly outperforms the other two training methods on 8-state secondary structure prediction and disorder prediction since their label distributions are highly imbalanced and also has similar performance as the other two training methods on solvent accessibility prediction, which has three equally-distributed labels. Furthermore, our experimental results show that our AUC-trained DeepCNF models greatly outperform existing popular predictors of these three tasks. The data and software related to this paper are available at https://github.com/realbigws/DeepCNF_AUC.

Comparison of least-squares vs. maximum likelihood estimation for standard spectrum technique of β−γ coincidence spectrum analysis

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.

Maximizers versus satisficers

Directory of Open Access Journals (Sweden)

Andrew M. Parker

2007-12-01

Full Text Available Our previous research suggests that people reporting a stronger desire to maximize obtain worse life outcomes (Bruine de Bruin et al., 2007. Here, we examine whether this finding may be explained by the decision-making styles of self-reported maximizers. Expanding on Schwartz et al. (2002, we find that self-reported maximizers are more likely to show problematic decision-making styles, as evidenced by self-reports of less behavioral coping, greater dependence on others when making decisions, more avoidance of decision making, and greater tendency to experience regret. Contrary to predictions, self-reported maximizers were more likely to report spontaneous decision making. However, the relationship between self-reported maximizing and worse life outcomes is largely unaffected by controls for measures of other decision-making styles, decision-making competence, and demographic variables.

Maximal slicing of D-dimensional spherically symmetric vacuum spacetime

International Nuclear Information System (INIS)

Nakao, Ken-ichi; Abe, Hiroyuki; Yoshino, Hirotaka; Shibata, Masaru

2009-01-01

We study the foliation of a D-dimensional spherically symmetric black-hole spacetime with D≥5 by two kinds of one-parameter families of maximal hypersurfaces: a reflection-symmetric foliation with respect to the wormhole slot and a stationary foliation that has an infinitely long trumpetlike shape. As in the four-dimensional case, the foliations by the maximal hypersurfaces avoid the singularity irrespective of the dimensionality. This indicates that the maximal slicing condition will be useful for simulating higher-dimensional black-hole spacetimes in numerical relativity. For the case of D=5, we present analytic solutions of the intrinsic metric, the extrinsic curvature, the lapse function, and the shift vector for the foliation by the stationary maximal hypersurfaces. These data will be useful for checking five-dimensional numerical-relativity codes based on the moving puncture approach.

The Laplace Likelihood Ratio Test for Heteroscedasticity

Directory of Open Access Journals (Sweden)

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.

Maximal hypersurfaces and foliations of constant mean curvature in general relativity

International Nuclear Information System (INIS)

Marsden, J.E.; Tipler, F.J.; Texas Univ., Austin

1980-01-01

We prove theorems on existence, uniqueness and smoothness of maximal and constant mean curvature compact spacelike hypersurfaces in globally hyperbolic spacetimes. The uniqueness theorem for maximal hypersurfaces of Brill and Flaherty, which assumed matter everywhere, is extended to specetimes that are vacuum and non-flat or that satisfy a generic-type condition. In this connection we show that under general hypotheses, a spatially closed universe with a maximal hypersurface must be Wheeler universe; i.e. be closed in time as well. The existence of Lipschitz achronal maximal volume hypersurfaces under the hypothesis that candidate hypersurfaces are bounded away from the singularity is proved. This hypothesis is shown to be valid in two cases of interest: when the singularities are of strong curvature type, and when the singularity is a single ideal point. Some properties of these maximal volume hypersurfaces and difficulties with Avez' original arguments are discussed. The difficulties involve the possibility that the maximal volume hypersurface can be null on certain portions; we present an incomplete argument which suggests that these hypersurfaces are always smooth, but prove that an a priori bound on the second fundamental form does imply smoothness. An extension of the perturbation theorem of Choquet-Bruhat, Fischer and Marsden is given and conditions under which local foliantions by constant mean curvature hypersurfaces can be extended to global ones is obtained. (orig.)

(Re)evaluating the Implications of the Autoregressive Latent Trajectory Model Through Likelihood Ratio Tests of Its Initial Conditions.

Science.gov (United States)

Ou, Lu; Chow, Sy-Miin; Ji, Linying; Molenaar, Peter C M

2017-01-01

The autoregressive latent trajectory (ALT) model synthesizes the autoregressive model and the latent growth curve model. The ALT model is flexible enough to produce a variety of discrepant model-implied change trajectories. While some researchers consider this a virtue, others have cautioned that this may confound interpretations of the model's parameters. In this article, we show that some-but not all-of these interpretational difficulties may be clarified mathematically and tested explicitly via likelihood ratio tests (LRTs) imposed on the initial conditions of the model. We show analytically the nested relations among three variants of the ALT model and the constraints needed to establish equivalences. A Monte Carlo simulation study indicated that LRTs, particularly when used in combination with information criterion measures, can allow researchers to test targeted hypotheses about the functional forms of the change process under study. We further demonstrate when and how such tests may justifiably be used to facilitate our understanding of the underlying process of change using a subsample (N = 3,995) of longitudinal family income data from the National Longitudinal Survey of Youth.

Developing maximal neuromuscular power: Part 1--biological basis of maximal power production.

Science.gov (United States)

Cormie, Prue; McGuigan, Michael R; Newton, Robert U

2011-01-01

This series of reviews focuses on the most important neuromuscular function in many sport performances, the ability to generate maximal muscular power. Part 1 focuses on the factors that affect maximal power production, while part 2, which will follow in a forthcoming edition of Sports Medicine, explores the practical application of these findings by reviewing the scientific literature relevant to the development of training programmes that most effectively enhance maximal power production. The ability of the neuromuscular system to generate maximal power is affected by a range of interrelated factors. Maximal muscular power is defined and limited by the force-velocity relationship and affected by the length-tension relationship. The ability to generate maximal power is influenced by the type of muscle action involved and, in particular, the time available to develop force, storage and utilization of elastic energy, interactions of contractile and elastic elements, potentiation of contractile and elastic filaments as well as stretch reflexes. Furthermore, maximal power production is influenced by morphological factors including fibre type contribution to whole muscle area, muscle architectural features and tendon properties as well as neural factors including motor unit recruitment, firing frequency, synchronization and inter-muscular coordination. In addition, acute changes in the muscle environment (i.e. alterations resulting from fatigue, changes in hormone milieu and muscle temperature) impact the ability to generate maximal power. Resistance training has been shown to impact each of these neuromuscular factors in quite specific ways. Therefore, an understanding of the biological basis of maximal power production is essential for developing training programmes that effectively enhance maximal power production in the human.

An efficient forward–reverse expectation-maximization algorithm for statistical inference in stochastic reaction networks

KAUST Repository

Bayer, Christian

2016-02-20

© 2016 Taylor & Francis Group, LLC. ABSTRACT: In this work, we present an extension of the forward–reverse representation introduced by Bayer and Schoenmakers (Annals of Applied Probability, 24(5):1994–2032, 2014) to the context of stochastic reaction networks (SRNs). We apply this stochastic representation to the computation of efficient approximations of expected values of functionals of SRN bridges, that is, SRNs conditional on their values in the extremes of given time intervals. We then employ this SRN bridge-generation technique to the statistical inference problem of approximating reaction propensities based on discretely observed data. To this end, we introduce a two-phase iterative inference method in which, during phase I, we solve a set of deterministic optimization problems where the SRNs are replaced by their reaction-rate ordinary differential equations approximation; then, during phase II, we apply the Monte Carlo version of the expectation-maximization algorithm to the phase I output. By selecting a set of overdispersed seeds as initial points in phase I, the output of parallel runs from our two-phase method is a cluster of approximate maximum likelihood estimates. Our results are supported by numerical examples.

Local Hamiltonians for maximally multipartite-entangled states

Science.gov (United States)

Facchi, P.; Florio, G.; Pascazio, S.; Pepe, F.

2010-10-01

We study the conditions for obtaining maximally multipartite-entangled states (MMESs) as nondegenerate eigenstates of Hamiltonians that involve only short-range interactions. We investigate small-size systems (with a number of qubits ranging from 3 to 5) and show some example Hamiltonians with MMESs as eigenstates.

Local Hamiltonians for maximally multipartite-entangled states

International Nuclear Information System (INIS)

Facchi, P.; Florio, G.; Pascazio, S.; Pepe, F.

2010-01-01

We study the conditions for obtaining maximally multipartite-entangled states (MMESs) as nondegenerate eigenstates of Hamiltonians that involve only short-range interactions. We investigate small-size systems (with a number of qubits ranging from 3 to 5) and show some example Hamiltonians with MMESs as eigenstates.

Comparison of IRT Likelihood Ratio Test and Logistic Regression DIF Detection Procedures

Science.gov (United States)

Atar, Burcu; Kamata, Akihito

2011-01-01

The Type I error rates and the power of IRT likelihood ratio test and cumulative logit ordinal logistic regression procedures in detecting differential item functioning (DIF) for polytomously scored items were investigated in this Monte Carlo simulation study. For this purpose, 54 simulation conditions (combinations of 3 sample sizes, 2 sample…

Corporate governance effect on financial distress likelihood: Evidence from Spain

Directory of Open Access Journals (Sweden)

Montserrat Manzaneque

2016-01-01

Full Text Available The paper explores some mechanisms of corporate governance (ownership and board characteristics in Spanish listed companies and their impact on the likelihood of financial distress. An empirical study was conducted between 2007 and 2012 using a matched-pairs research design with 308 observations, with half of them classified as distressed and non-distressed. Based on the previous study by Pindado, Rodrigues, and De la Torre (2008, a broader concept of bankruptcy is used to define business failure. Employing several conditional logistic models, as well as to other previous studies on bankruptcy, the results confirm that in difficult situations prior to bankruptcy, the impact of board ownership and proportion of independent directors on business failure likelihood are similar to those exerted in more extreme situations. These results go one step further, to offer a negative relationship between board size and the likelihood of financial distress. This result is interpreted as a form of creating diversity and to improve the access to the information and resources, especially in contexts where the ownership is highly concentrated and large shareholders have a great power to influence the board structure. However, the results confirm that ownership concentration does not have a significant impact on financial distress likelihood in the Spanish context. It is argued that large shareholders are passive as regards an enhanced monitoring of management and, alternatively, they do not have enough incentives to hold back the financial distress. These findings have important implications in the Spanish context, where several changes in the regulatory listing requirements have been carried out with respect to corporate governance, and where there is no empirical evidence regarding this respect.

Dynamic Convex Duality in Constrained Utility Maximization

OpenAIRE

Li, Yusong; Zheng, Harry

2016-01-01

In this paper, we study a constrained utility maximization problem following the convex duality approach. After formulating the primal and dual problems, we construct the necessary and sufficient conditions for both the primal and dual problems in terms of FBSDEs plus additional conditions. Such formulation then allows us to explicitly characterize the primal optimal control as a function of the adjoint process coming from the dual FBSDEs in a dynamic fashion and vice versa. Moreover, we also...

Expectation Maximization Algorithm for Box-Cox Transformation Cure Rate Model and Assessment of Model Misspecification Under Weibull Lifetimes.

Science.gov (United States)

Pal, Suvra; Balakrishnan, Narayanaswamy

2018-05-01

In this paper, we develop likelihood inference based on the expectation maximization algorithm for the Box-Cox transformation cure rate model assuming the lifetimes to follow a Weibull distribution. A simulation study is carried out to demonstrate the performance of the proposed estimation method. Through Monte Carlo simulations, we also study the effect of model misspecification on the estimate of cure rate. Finally, we analyze a well-known data on melanoma with the model and the inferential method developed here.

Maximizers versus satisficers

OpenAIRE

Andrew M. Parker; Wandi Bruine de Bruin; Baruch Fischhoff

2007-01-01

Our previous research suggests that people reporting a stronger desire to maximize obtain worse life outcomes (Bruine de Bruin et al., 2007). Here, we examine whether this finding may be explained by the decision-making styles of self-reported maximizers. Expanding on Schwartz et al. (2002), we find that self-reported maximizers are more likely to show problematic decision-making styles, as evidenced by self-reports of less behavioral coping, greater dependence on others when making decisions...

Improving a gold standard: treating human relevance judgments of MEDLINE document pairs

Directory of Open Access Journals (Sweden)

Kim Won

2011-06-01

Full Text Available Abstract Given prior human judgments of the condition of an object it is possible to use these judgments to make a maximal likelihood estimate of what future human judgments of the condition of that object will be. However, if one has a reasonably large collection of similar objects and the prior human judgments of a number of judges regarding the condition of each object in the collection, then it is possible to make predictions of future human judgments for the whole collection that are superior to the simple maximal likelihood estimate for each object in isolation. This is possible because the multiple judgments over the collection allow an analysis to determine the relative value of a judge as compared with the other judges in the group and this value can be used to augment or diminish a particular judge’s influence in predicting future judgments. Here we study and compare five different methods for making such improved predictions and show that each is superior to simple maximal likelihood estimates.

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

Maximum-Likelihood Detection Of Noncoherent CPM

Science.gov (United States)

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.

Likelihood analysis of parity violation in the compound nucleus

International Nuclear Information System (INIS)

Bowman, D.; Sharapov, E.

1993-01-01

We discuss the determination of the root mean-squared matrix element of the parity-violating interaction between compound-nuclear states using likelihood analysis. We briefly review the relevant features of the statistical model of the compound nucleus and the formalism of likelihood analysis. We then discuss the application of likelihood analysis to data on panty-violating longitudinal asymmetries. The reliability of the extracted value of the matrix element and errors assigned to the matrix element is stressed. We treat the situations where the spins of the p-wave resonances are not known and known using experimental data and Monte Carlo techniques. We conclude that likelihood analysis provides a reliable way to determine M and its confidence interval. We briefly discuss some problems associated with the normalization of the likelihood function

An Expectation-Maximization Method for Calibrating Synchronous Machine Models

Energy Technology Data Exchange (ETDEWEB)

Meng, Da; Zhou, Ning; Lu, Shuai; Lin, Guang

2013-07-21

The accuracy of a power system dynamic model is essential to its secure and efficient operation. Lower confidence in model accuracy usually leads to conservative operation and lowers asset usage. To improve model accuracy, this paper proposes an expectation-maximization (EM) method to calibrate the synchronous machine model using phasor measurement unit (PMU) data. First, an extended Kalman filter (EKF) is applied to estimate the dynamic states using measurement data. Then, the parameters are calculated based on the estimated states using maximum likelihood estimation (MLE) method. The EM method iterates over the preceding two steps to improve estimation accuracy. The proposed EM method’s performance is evaluated using a single-machine infinite bus system and compared with a method where both state and parameters are estimated using an EKF method. Sensitivity studies of the parameter calibration using EM method are also presented to show the robustness of the proposed method for different levels of measurement noise and initial parameter uncertainty.

Entropy maximization

Indian Academy of Sciences (India)

Abstract. It is shown that (i) every probability density is the unique maximizer of relative entropy in an appropriate class and (ii) in the class of all pdf f that satisfy. ∫ fhi dμ = λi for i = 1, 2,...,...k the maximizer of entropy is an f0 that is pro- portional to exp(. ∑ ci hi ) for some choice of ci . An extension of this to a continuum of.

Similar tests and the standardized log likelihood ratio statistic

DEFF Research Database (Denmark)

Jensen, Jens Ledet

1986-01-01

When testing an affine hypothesis in an exponential family the 'ideal' procedure is to calculate the exact similar test, or an approximation to this, based on the conditional distribution given the minimal sufficient statistic under the null hypothesis. By contrast to this there is a 'primitive......' approach in which the marginal distribution of a test statistic considered and any nuisance parameter appearing in the test statistic is replaced by an estimate. We show here that when using standardized likelihood ratio statistics the 'primitive' procedure is in fact an 'ideal' procedure to order O(n -3...

The numerical evaluation of maximum-likelihood estimates of the parameters for a mixture of normal distributions from partially identified samples

Science.gov (United States)

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.

Efficacy of manual versus free-weight training to improve maximal strength and performance for microgravity conditions.

Science.gov (United States)

Behringer, Michael; Schüren, Thomas; McCourt, Molly; Mester, Joachim

2016-01-01

We tested a simple and compact device designed for manual resistance training in conditions of microgravity (Self-Powered Rope Trainer Duo (SPoRT Duo)) to increase muscle performance. Twenty-four participants (20.8 ± 2.1 years) were randomly assigned to a manual resistance group (n = 12) and a free-weight group (n = 12). Participants performed eight exercises (three sets; 8-12 efforts) either with free weights or the SPoRT Duo twice a week for 6 weeks. Maximal isometric force of trunk flexion, back extension and chest press increased (P at least 0.01, d at least 0.52) both in the manual resistance group (18.4% ± 15.0%; 32.7% ± 22.7%; 15.3% ± 9.7%) and free-weight group (18.0% ± 13.9%; 26.6% ± 28.9%; 13.3% ± 7.6%). The change in maximal isometric force of wide grip row in both groups (d at best 0.38) did not reach statistical significance (P at best 0.08). The squat one-repetition-maximum increased in the manual resistance group (29.8% ± 22.1%) and the free-weight group (32.4% ± 26.6%). Jump height, determined by a jump-and-reach test, increased in the free-weight group (9.8% ± 13.2%) but not in the manual resistance group (2.0% ± 8.5%). Manual resistance training was equally effective in increasing strength as traditional resistance training with free weights. This apparatus is a useful addition to current in-flight exercise systems.

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

Effect of sonic driving on maximal aerobic performance.

Science.gov (United States)

Brilla, L.R.; Hatcher, Stefanie

2000-07-01

The study purpose was to evaluate antecedent binaural stimulation (ABS) on maximal aerobic physical performance. Twenty-two healthy, physically active subjects, 21-34 years, randomly received one of two preparations for each session: 15 min of quiet (BLANK) or percussive sonic driving at 200+ beats per minute (bpm) using a recorded compact disc (FSS, Mill Valley, CA) with headphones (ABS). Baseline HR, blood pressure (BP), and breathing frequency (f(br)) were obtained. During each condition, HR and f(br) were recorded at 3-min intervals. The graded maximal treadmill testing was administered immediately postpreparation session on separate days, with at least 48 h rest between sessions. There were significant differences in the antecedent period means between the two conditions, ABS (HR: 70.2 +/- 10.7 bpm; f(br): 18.5 +/- 3.3 br min(-1); BP: 134.5/87.9 +/- 13.6/9.2 mm Hg) and BLANK (HR: 64.6 +/- 7.9; f(br): 14.3 +/- 2.9; BP: 126.7/80.3 +/- 12.1/8.6). Differences were noted for each 3-min interval and pre- postantecedent period. The maximal graded exercise test (GXT) results showed that there was a small but significant (P 0.05). There may be a latency to ABS related to entrainment or imagery-enhanced warm-up. Am. J. Hum. Biol. 12:558-565, 2000. Copyright 2000 Wiley-Liss, Inc.

Entropy Maximization

Indian Academy of Sciences (India)

It is shown that (i) every probability density is the unique maximizer of relative entropy in an appropriate class and (ii) in the class of all pdf that satisfy ∫ f h i d = i for i = 1 , 2 , … , … k the maximizer of entropy is an f 0 that is proportional to exp ⁡ ( ∑ c i h i ) for some choice of c i . An extension of this to a continuum of ...

Greenery in the university environment: Students’ preferences and perceived restoration likelihood

Science.gov (United States)

2018-01-01

A large body of evidence shows that interaction with greenery can be beneficial for human stress reduction, emotional states, and improved cognitive function. It can, therefore, be expected that university students might benefit from greenery in the university environment. Before investing in real-life interventions in a university environment, it is necessary to first explore students’ perceptions of greenery in the university environment. This study examined (1) preference for university indoor and outdoor spaces with and without greenery (2) perceived restoration likelihood of university outdoor spaces with and without greenery and (3) if preference and perceived restoration likelihood ratings were modified by demographic characteristics or connectedness to nature in Dutch university students (N = 722). Digital photographic stimuli represented four university spaces (lecture hall, classroom, study area, university outdoor space). For each of the three indoor spaces there were four or five stimuli conditions: (1) the standard design (2) the standard design with a colorful poster (3) the standard design with a nature poster (4) the standard design with a green wall (5) the standard design with a green wall plus interior plants. The university outdoor space included: (1) the standard design (2) the standard design with seating (3) the standard design with colorful artifacts (4) the standard design with green elements (5) the standard design with extensive greenery. Multi-level analyses showed that students gave higher preference ratings to the indoor spaces with a nature poster, a green wall, or a green wall plus interior plants than to the standard designs and the designs with the colorful posters. Students also rated preference and perceived restoration likelihood of the outdoor spaces that included greenery higher than those without. Preference and perceived restoration likelihood were not modified by demographic characteristics, but students with strong

Greenery in the university environment: Students' preferences and perceived restoration likelihood.

Directory of Open Access Journals (Sweden)

Nicole van den Bogerd

Full Text Available A large body of evidence shows that interaction with greenery can be beneficial for human stress reduction, emotional states, and improved cognitive function. It can, therefore, be expected that university students might benefit from greenery in the university environment. Before investing in real-life interventions in a university environment, it is necessary to first explore students' perceptions of greenery in the university environment. This study examined (1 preference for university indoor and outdoor spaces with and without greenery (2 perceived restoration likelihood of university outdoor spaces with and without greenery and (3 if preference and perceived restoration likelihood ratings were modified by demographic characteristics or connectedness to nature in Dutch university students (N = 722. Digital photographic stimuli represented four university spaces (lecture hall, classroom, study area, university outdoor space. For each of the three indoor spaces there were four or five stimuli conditions: (1 the standard design (2 the standard design with a colorful poster (3 the standard design with a nature poster (4 the standard design with a green wall (5 the standard design with a green wall plus interior plants. The university outdoor space included: (1 the standard design (2 the standard design with seating (3 the standard design with colorful artifacts (4 the standard design with green elements (5 the standard design with extensive greenery. Multi-level analyses showed that students gave higher preference ratings to the indoor spaces with a nature poster, a green wall, or a green wall plus interior plants than to the standard designs and the designs with the colorful posters. Students also rated preference and perceived restoration likelihood of the outdoor spaces that included greenery higher than those without. Preference and perceived restoration likelihood were not modified by demographic characteristics, but students with strong

Greenery in the university environment: Students' preferences and perceived restoration likelihood.

Science.gov (United States)

van den Bogerd, Nicole; Dijkstra, S Coosje; Seidell, Jacob C; Maas, Jolanda

2018-01-01

A large body of evidence shows that interaction with greenery can be beneficial for human stress reduction, emotional states, and improved cognitive function. It can, therefore, be expected that university students might benefit from greenery in the university environment. Before investing in real-life interventions in a university environment, it is necessary to first explore students' perceptions of greenery in the university environment. This study examined (1) preference for university indoor and outdoor spaces with and without greenery (2) perceived restoration likelihood of university outdoor spaces with and without greenery and (3) if preference and perceived restoration likelihood ratings were modified by demographic characteristics or connectedness to nature in Dutch university students (N = 722). Digital photographic stimuli represented four university spaces (lecture hall, classroom, study area, university outdoor space). For each of the three indoor spaces there were four or five stimuli conditions: (1) the standard design (2) the standard design with a colorful poster (3) the standard design with a nature poster (4) the standard design with a green wall (5) the standard design with a green wall plus interior plants. The university outdoor space included: (1) the standard design (2) the standard design with seating (3) the standard design with colorful artifacts (4) the standard design with green elements (5) the standard design with extensive greenery. Multi-level analyses showed that students gave higher preference ratings to the indoor spaces with a nature poster, a green wall, or a green wall plus interior plants than to the standard designs and the designs with the colorful posters. Students also rated preference and perceived restoration likelihood of the outdoor spaces that included greenery higher than those without. Preference and perceived restoration likelihood were not modified by demographic characteristics, but students with strong

Maintaining symmetry of simulated likelihood functions

DEFF Research Database (Denmark)

Andersen, Laura Mørch

This paper suggests solutions to two different types of simulation errors related to Quasi-Monte Carlo integration. Likelihood functions which depend on standard deviations of mixed parameters are symmetric in nature. This paper shows that antithetic draws preserve this symmetry and thereby...... improves precision substantially. Another source of error is that models testing away mixing dimensions must replicate the relevant dimensions of the quasi-random draws in the simulation of the restricted likelihood. These simulation errors are ignored in the standard estimation procedures used today...

Maximally incompatible quantum observables

Energy Technology Data Exchange (ETDEWEB)

Heinosaari, Teiko, E-mail: teiko.heinosaari@utu.fi [Turku Centre for Quantum Physics, Department of Physics and Astronomy, University of Turku, FI-20014 Turku (Finland); Schultz, Jussi, E-mail: jussi.schultz@gmail.com [Dipartimento di Matematica, Politecnico di Milano, Piazza Leonardo da Vinci 32, I-20133 Milano (Italy); Toigo, Alessandro, E-mail: alessandro.toigo@polimi.it [Dipartimento di Matematica, Politecnico di Milano, Piazza Leonardo da Vinci 32, I-20133 Milano (Italy); Istituto Nazionale di Fisica Nucleare, Sezione di Milano, Via Celoria 16, I-20133 Milano (Italy); Ziman, Mario, E-mail: ziman@savba.sk [RCQI, Institute of Physics, Slovak Academy of Sciences, Dúbravská cesta 9, 84511 Bratislava (Slovakia); Faculty of Informatics, Masaryk University, Botanická 68a, 60200 Brno (Czech Republic)

2014-05-01

The existence of maximally incompatible quantum observables in the sense of a minimal joint measurability region is investigated. Employing the universal quantum cloning device it is argued that only infinite dimensional quantum systems can accommodate maximal incompatibility. It is then shown that two of the most common pairs of complementary observables (position and momentum; number and phase) are maximally incompatible.

Maximally incompatible quantum observables

International Nuclear Information System (INIS)

Heinosaari, Teiko; Schultz, Jussi; Toigo, Alessandro; Ziman, Mario

2014-01-01

The existence of maximally incompatible quantum observables in the sense of a minimal joint measurability region is investigated. Employing the universal quantum cloning device it is argued that only infinite dimensional quantum systems can accommodate maximal incompatibility. It is then shown that two of the most common pairs of complementary observables (position and momentum; number and phase) are maximally incompatible.

Solutions to the maximal spacelike hypersurface equation in generalized Robertson-Walker spacetimes

Directory of Open Access Journals (Sweden)

Henrique F. de Lima

2018-03-01

Full Text Available We apply some generalized maximum principles for establishing uniqueness and nonexistence results concerning maximal spacelike hypersurfaces immersed in a generalized Robertson-Walker (GRW spacetime, which is supposed to obey the so-called timelike convergence condition (TCC. As application, we study the uniqueness and nonexistence of entire solutions of a suitable maximal spacelike hypersurface equation in GRW spacetimes obeying the TCC.

Penalized likelihood and multi-objective spatial scans for the detection and inference of irregular clusters

Directory of Open Access Journals (Sweden)

Fonseca Carlos M

2010-10-01

Full Text Available Abstract Background Irregularly shaped spatial clusters are difficult to delineate. A cluster found by an algorithm often spreads through large portions of the map, impacting its geographical meaning. Penalized likelihood methods for Kulldorff's spatial scan statistics have been used to control the excessive freedom of the shape of clusters. Penalty functions based on cluster geometry and non-connectivity have been proposed recently. Another approach involves the use of a multi-objective algorithm to maximize two objectives: the spatial scan statistics and the geometric penalty function. Results & Discussion We present a novel scan statistic algorithm employing a function based on the graph topology to penalize the presence of under-populated disconnection nodes in candidate clusters, the disconnection nodes cohesion function. A disconnection node is defined as a region within a cluster, such that its removal disconnects the cluster. By applying this function, the most geographically meaningful clusters are sifted through the immense set of possible irregularly shaped candidate cluster solutions. To evaluate the statistical significance of solutions for multi-objective scans, a statistical approach based on the concept of attainment function is used. In this paper we compared different penalized likelihoods employing the geometric and non-connectivity regularity functions and the novel disconnection nodes cohesion function. We also build multi-objective scans using those three functions and compare them with the previous penalized likelihood scans. An application is presented using comprehensive state-wide data for Chagas' disease in puerperal women in Minas Gerais state, Brazil. Conclusions We show that, compared to the other single-objective algorithms, multi-objective scans present better performance, regarding power, sensitivity and positive predicted value. The multi-objective non-connectivity scan is faster and better suited for the

Cardiorespiratory Coordination in Repeated Maximal Exercise

Directory of Open Access Journals (Sweden)

Sergi Garcia-Retortillo

2017-06-01

Full Text Available Increases in cardiorespiratory coordination (CRC after training with no differences in performance and physiological variables have recently been reported using a principal component analysis approach. However, no research has yet evaluated the short-term effects of exercise on CRC. The aim of this study was to delineate the behavior of CRC under different physiological initial conditions produced by repeated maximal exercises. Fifteen participants performed 2 consecutive graded and maximal cycling tests. Test 1 was performed without any previous exercise, and Test 2 6 min after Test 1. Both tests started at 0 W and the workload was increased by 25 W/min in males and 20 W/min in females, until they were not able to maintain the prescribed cycling frequency of 70 rpm for more than 5 consecutive seconds. A principal component (PC analysis of selected cardiovascular and cardiorespiratory variables (expired fraction of O2, expired fraction of CO2, ventilation, systolic blood pressure, diastolic blood pressure, and heart rate was performed to evaluate the CRC defined by the number of PCs in both tests. In order to quantify the degree of coordination, the information entropy was calculated and the eigenvalues of the first PC (PC1 were compared between tests. Although no significant differences were found between the tests with respect to the performed maximal workload (Wmax, maximal oxygen consumption (VO2 max, or ventilatory threshold (VT, an increase in the number of PCs and/or a decrease of eigenvalues of PC1 (t = 2.95; p = 0.01; d = 1.08 was found in Test 2 compared to Test 1. Moreover, entropy was significantly higher (Z = 2.33; p = 0.02; d = 1.43 in the last test. In conclusion, despite the fact that no significant differences were observed in the conventionally explored maximal performance and physiological variables (Wmax, VO2 max, and VT between tests, a reduction of CRC was observed in Test 2. These results emphasize the interest of CRC

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...

Likelihood inference for COM-Poisson cure rate model with interval-censored data and Weibull lifetimes.

Science.gov (United States)

Pal, Suvra; Balakrishnan, N

2017-10-01

In this paper, we consider a competing cause scenario and assume the number of competing causes to follow a Conway-Maxwell Poisson distribution which can capture both over and under dispersion that is usually encountered in discrete data. Assuming the population of interest having a component cure and the form of the data to be interval censored, as opposed to the usually considered right-censored data, the main contribution is in developing the steps of the expectation maximization algorithm for the determination of the maximum likelihood estimates of the model parameters of the flexible Conway-Maxwell Poisson cure rate model with Weibull lifetimes. An extensive Monte Carlo simulation study is carried out to demonstrate the performance of the proposed estimation method. Model discrimination within the Conway-Maxwell Poisson distribution is addressed using the likelihood ratio test and information-based criteria to select a suitable competing cause distribution that provides the best fit to the data. A simulation study is also carried out to demonstrate the loss in efficiency when selecting an improper competing cause distribution which justifies the use of a flexible family of distributions for the number of competing causes. Finally, the proposed methodology and the flexibility of the Conway-Maxwell Poisson distribution are illustrated with two known data sets from the literature: smoking cessation data and breast cosmesis data.

Computation of the Likelihood in Biallelic Diffusion Models Using Orthogonal Polynomials

Directory of Open Access Journals (Sweden)

Claus Vogl

2014-11-01

Full Text Available In population genetics, parameters describing forces such as mutation, migration and drift are generally inferred from molecular data. Lately, approximate methods based on simulations and summary statistics have been widely applied for such inference, even though these methods waste information. In contrast, probabilistic methods of inference can be shown to be optimal, if their assumptions are met. In genomic regions where recombination rates are high relative to mutation rates, polymorphic nucleotide sites can be assumed to evolve independently from each other. The distribution of allele frequencies at a large number of such sites has been called “allele-frequency spectrum” or “site-frequency spectrum” (SFS. Conditional on the allelic proportions, the likelihoods of such data can be modeled as binomial. A simple model representing the evolution of allelic proportions is the biallelic mutation-drift or mutation-directional selection-drift diffusion model. With series of orthogonal polynomials, specifically Jacobi and Gegenbauer polynomials, or the related spheroidal wave function, the diffusion equations can be solved efficiently. In the neutral case, the product of the binomial likelihoods with the sum of such polynomials leads to finite series of polynomials, i.e., relatively simple equations, from which the exact likelihoods can be calculated. In this article, the use of orthogonal polynomials for inferring population genetic parameters is investigated.

Maximal combustion temperature estimation

International Nuclear Information System (INIS)

Golodova, E; Shchepakina, E

2006-01-01

This work is concerned with the phenomenon of delayed loss of stability and the estimation of the maximal temperature of safe combustion. Using the qualitative theory of singular perturbations and canard techniques we determine the maximal temperature on the trajectories located in the transition region between the slow combustion regime and the explosive one. This approach is used to estimate the maximal temperature of safe combustion in multi-phase combustion models

Conditional probability distribution associated to the E-M image reconstruction algorithm for neutron stimulated emission tomography

International Nuclear Information System (INIS)

Viana, R.S.; Yoriyaz, H.; Santos, A.

2011-01-01

The Expectation-Maximization (E-M) algorithm is an iterative computational method for maximum likelihood (M-L) estimates, useful in a variety of incomplete-data problems. Due to its stochastic nature, one of the most relevant applications of E-M algorithm is the reconstruction of emission tomography images. In this paper, the statistical formulation of the E-M algorithm was applied to the in vivo spectrographic imaging of stable isotopes called Neutron Stimulated Emission Computed Tomography (NSECT). In the process of E-M algorithm iteration, the conditional probability distribution plays a very important role to achieve high quality image. This present work proposes an alternative methodology for the generation of the conditional probability distribution associated to the E-M reconstruction algorithm, using the Monte Carlo code MCNP5 and with the application of the reciprocity theorem. (author)

Conditional probability distribution associated to the E-M image reconstruction algorithm for neutron stimulated emission tomography

Energy Technology Data Exchange (ETDEWEB)

Viana, R.S.; Yoriyaz, H.; Santos, A., E-mail: rodrigossviana@gmail.com, E-mail: hyoriyaz@ipen.br, E-mail: asantos@ipen.br [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)

2011-07-01

The Expectation-Maximization (E-M) algorithm is an iterative computational method for maximum likelihood (M-L) estimates, useful in a variety of incomplete-data problems. Due to its stochastic nature, one of the most relevant applications of E-M algorithm is the reconstruction of emission tomography images. In this paper, the statistical formulation of the E-M algorithm was applied to the in vivo spectrographic imaging of stable isotopes called Neutron Stimulated Emission Computed Tomography (NSECT). In the process of E-M algorithm iteration, the conditional probability distribution plays a very important role to achieve high quality image. This present work proposes an alternative methodology for the generation of the conditional probability distribution associated to the E-M reconstruction algorithm, using the Monte Carlo code MCNP5 and with the application of the reciprocity theorem. (author)

Likelihood ratio sequential sampling models of recognition memory.

Science.gov (United States)

Osth, Adam F; Dennis, Simon; Heathcote, Andrew

2017-02-01

The mirror effect - a phenomenon whereby a manipulation produces opposite effects on hit and false alarm rates - is benchmark regularity of recognition memory. A likelihood ratio decision process, basing recognition on the relative likelihood that a stimulus is a target or a lure, naturally predicts the mirror effect, and so has been widely adopted in quantitative models of recognition memory. Glanzer, Hilford, and Maloney (2009) demonstrated that likelihood ratio models, assuming Gaussian memory strength, are also capable of explaining regularities observed in receiver-operating characteristics (ROCs), such as greater target than lure variance. Despite its central place in theorising about recognition memory, however, this class of models has not been tested using response time (RT) distributions. In this article, we develop a linear approximation to the likelihood ratio transformation, which we show predicts the same regularities as the exact transformation. This development enabled us to develop a tractable model of recognition-memory RT based on the diffusion decision model (DDM), with inputs (drift rates) provided by an approximate likelihood ratio transformation. We compared this "LR-DDM" to a standard DDM where all targets and lures receive their own drift rate parameters. Both were implemented as hierarchical Bayesian models and applied to four datasets. Model selection taking into account parsimony favored the LR-DDM, which requires fewer parameters than the standard DDM but still fits the data well. These results support log-likelihood based models as providing an elegant explanation of the regularities of recognition memory, not only in terms of choices made but also in terms of the times it takes to make them. Copyright © 2016 Elsevier Inc. All rights reserved.

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...

High-order Composite Likelihood Inference for Max-Stable Distributions and Processes

KAUST Repository

Castruccio, Stefano; Huser, Raphaë l; Genton, Marc G.

2015-01-01

In multivariate or spatial extremes, inference for max-stable processes observed at a large collection of locations is a very challenging problem in computational statistics, and current approaches typically rely on less expensive composite likelihoods constructed from small subsets of data. In this work, we explore the limits of modern state-of-the-art computational facilities to perform full likelihood inference and to efficiently evaluate high-order composite likelihoods. With extensive simulations, we assess the loss of information of composite likelihood estimators with respect to a full likelihood approach for some widely-used multivariate or spatial extreme models, we discuss how to choose composite likelihood truncation to improve the efficiency, and we also provide recommendations for practitioners. This article has supplementary material online.

High-order Composite Likelihood Inference for Max-Stable Distributions and Processes

KAUST Repository

Castruccio, Stefano

2015-09-29

In multivariate or spatial extremes, inference for max-stable processes observed at a large collection of locations is a very challenging problem in computational statistics, and current approaches typically rely on less expensive composite likelihoods constructed from small subsets of data. In this work, we explore the limits of modern state-of-the-art computational facilities to perform full likelihood inference and to efficiently evaluate high-order composite likelihoods. With extensive simulations, we assess the loss of information of composite likelihood estimators with respect to a full likelihood approach for some widely-used multivariate or spatial extreme models, we discuss how to choose composite likelihood truncation to improve the efficiency, and we also provide recommendations for practitioners. This article has supplementary material online.

Earthquake likelihood model testing

Science.gov (United States)

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

Phylogenetic analysis using parsimony and likelihood methods.

Science.gov (United States)

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

AUC-Maximizing Ensembles through Metalearning.

Science.gov (United States)

LeDell, Erin; van der Laan, Mark J; Petersen, Maya

2016-05-01

Area Under the ROC Curve (AUC) is often used to measure the performance of an estimator in binary classification problems. An AUC-maximizing classifier can have significant advantages in cases where ranking correctness is valued or if the outcome is rare. In a Super Learner ensemble, maximization of the AUC can be achieved by the use of an AUC-maximining metalearning algorithm. We discuss an implementation of an AUC-maximization technique that is formulated as a nonlinear optimization problem. We also evaluate the effectiveness of a large number of different nonlinear optimization algorithms to maximize the cross-validated AUC of the ensemble fit. The results provide evidence that AUC-maximizing metalearners can, and often do, out-perform non-AUC-maximizing metalearning methods, with respect to ensemble AUC. The results also demonstrate that as the level of imbalance in the training data increases, the Super Learner ensemble outperforms the top base algorithm by a larger degree.

Analysis of hourly crash likelihood using unbalanced panel data mixed logit model and real-time driving environmental big data.

Science.gov (United States)

Chen, Feng; Chen, Suren; Ma, Xiaoxiang

2018-06-01

Driving environment, including road surface conditions and traffic states, often changes over time and influences crash probability considerably. It becomes stretched for traditional crash frequency models developed in large temporal scales to capture the time-varying characteristics of these factors, which may cause substantial loss of critical driving environmental information on crash prediction. Crash prediction models with refined temporal data (hourly records) are developed to characterize the time-varying nature of these contributing factors. Unbalanced panel data mixed logit models are developed to analyze hourly crash likelihood of highway segments. The refined temporal driving environmental data, including road surface and traffic condition, obtained from the Road Weather Information System (RWIS), are incorporated into the models. Model estimation results indicate that the traffic speed, traffic volume, curvature and chemically wet road surface indicator are better modeled as random parameters. The estimation results of the mixed logit models based on unbalanced panel data show that there are a number of factors related to crash likelihood on I-25. Specifically, weekend indicator, November indicator, low speed limit and long remaining service life of rutting indicator are found to increase crash likelihood, while 5-am indicator and number of merging ramps per lane per mile are found to decrease crash likelihood. The study underscores and confirms the unique and significant impacts on crash imposed by the real-time weather, road surface, and traffic conditions. With the unbalanced panel data structure, the rich information from real-time driving environmental big data can be well incorporated. Copyright © 2018 National Safety Council and Elsevier Ltd. All rights reserved.

MAXIMIZING HYDROPOWER PRODUCTION FROM RESERVOIRS:THE CASE STUDY OF MARKABA

International Nuclear Information System (INIS)

Jaafar, H.

2014-01-01

Hydropower is a form of renewable energy that is clean and cheap. Under uncertain climatic conditions, maximization of hydropower production becomes a challenging task.Stochastic Dynamic programming (SDP) is a promising optimization algorithm that is usedfor complex non-linear reservoir operational policies and strategies.In this research, a combined simulation-SDPoptimization model isdeveloped andverified for maximizing large-scale hydropower production in a monthly time step. The model isdeveloped to generate optimal operational policies for the Qarawn reservoir in Lebanon and test these policies in real time conditions. The model isused to derive operational regimes for the Qarawn reservoirunder varying flows using transitional probability matrices. Simulating the derived rules and the generated operational policies proved effective in maximizingthe hydropower production from the Markaba power plant. The model could be successfully applied to other hydropower dams in the region. (author)

Is CP violation maximal

International Nuclear Information System (INIS)

Gronau, M.

1984-01-01

Two ambiguities are noted in the definition of the concept of maximal CP violation. The phase convention ambiguity is overcome by introducing a CP violating phase in the quark mixing matrix U which is invariant under rephasing transformations. The second ambiguity, related to the parametrization of U, is resolved by finding a single empirically viable definition of maximal CP violation when assuming that U does not single out one generation. Considerable improvement in the calculation of nonleptonic weak amplitudes is required to test the conjecture of maximal CP violation. 21 references

Shareholder, stakeholder-owner or broad stakeholder maximization

OpenAIRE

Mygind, Niels

2004-01-01

With reference to the discussion about shareholder versus stakeholder maximization it is argued that the normal type of maximization is in fact stakeholder-owner maxi-mization. This means maximization of the sum of the value of the shares and stake-holder benefits belonging to the dominating stakeholder-owner. Maximization of shareholder value is a special case of owner-maximization, and only under quite re-strictive assumptions shareholder maximization is larger or equal to stakeholder-owner...

The modified signed likelihood statistic and saddlepoint approximations

DEFF Research Database (Denmark)

Jensen, Jens Ledet

1992-01-01

SUMMARY: For a number of tests in exponential families we show that the use of a normal approximation to the modified signed likelihood ratio statistic r * is equivalent to the use of a saddlepoint approximation. This is also true in a large deviation region where the signed likelihood ratio...... statistic r is of order √ n. © 1992 Biometrika Trust....

Gamma loop contributing to maximal voluntary contractions in man.

Science.gov (United States)

Hagbarth, K E; Kunesch, E J; Nordin, M; Schmidt, R; Wallin, E U

1986-01-01

A local anaesthetic drug was injected around the peroneal nerve in healthy subjects in order to investigate whether the resulting loss in foot dorsiflexion power in part depended on a gamma-fibre block preventing 'internal' activation of spindle end-organs and thereby depriving the alpha-motoneurones of an excitatory spindle inflow during contraction. The motor outcome of maximal dorsiflexion efforts was assessed by measuring firing rates of individual motor units in the anterior tibial (t.a.) muscle, mean voltage e.m.g. from the pretibial muscles, dorsiflexion force and range of voluntary foot dorsiflexion movements. The tests were performed with and without peripheral conditioning stimuli, such as agonist or antagonist muscle vibration or imposed stretch of the contracting muscles. As compared to control values of t.a. motor unit firing rates in maximal isometric voluntary contractions, the firing rates were lower and more irregular during maximal dorsiflexion efforts performed during subtotal peroneal nerve blocks. During the development of paresis a gradual reduction of motor unit firing rates was observed before the units ceased responding to the voluntary commands. This change in motor unit behaviour was accompanied by a reduction of the mean voltage e.m.g. activity in the pretibial muscles. At a given stage of anaesthesia the e.m.g. responses to maximal voluntary efforts were more affected than the responses evoked by electric nerve stimuli delivered proximal to the block, indicating that impaired impulse transmission in alpha motor fibres was not the sole cause of the paresis. The inability to generate high and regular motor unit firing rates during peroneal nerve blocks was accentuated by vibration applied over the antagonistic calf muscles. By contrast, in eight out of ten experiments agonist stretch or vibration caused an enhancement of motor unit firing during the maximal force tasks. The reverse effects of agonist and antagonist vibration on the

Planck intermediate results: XVI. Profile likelihoods for cosmological parameters

DEFF Research Database (Denmark)

Bartlett, J.G.; Cardoso, J.-F.; Delabrouille, J.

2014-01-01

We explore the 2013 Planck likelihood function with a high-precision multi-dimensional minimizer (Minuit). This allows a refinement of the CDM best-fit solution with respect to previously-released results, and the construction of frequentist confidence intervals using profile likelihoods. The agr...

Planck 2013 results. XV. CMB power spectra and likelihood

DEFF Research Database (Denmark)

Tauber, Jan; Bartlett, J.G.; Bucher, M.

2014-01-01

This paper presents the Planck 2013 likelihood, a complete statistical description of the two-point correlation function of the CMB temperature fluctuations that accounts for all known relevant uncertainties, both instrumental and astrophysical in nature. We use this likelihood to derive our best...

The behavior of the likelihood ratio test for testing missingness

OpenAIRE

Hens, Niel; Aerts, Marc; Molenberghs, Geert; Thijs, Herbert

2003-01-01

To asses the sensitivity of conclusions to model choices in the context of selection models for non-random dropout, one can oppose the different missing mechanisms to each other; e.g. by the likelihood ratio tests. The finite sample behavior of the null distribution and the power of the likelihood ratio test is studied under a variety of missingness mechanisms. missing data; sensitivity analysis; likelihood ratio test; missing mechanisms

Ego involvement increases doping likelihood.

Science.gov (United States)

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.

Task-oriented maximally entangled states

International Nuclear Information System (INIS)

Agrawal, Pankaj; Pradhan, B

2010-01-01

We introduce the notion of a task-oriented maximally entangled state (TMES). This notion depends on the task for which a quantum state is used as the resource. TMESs are the states that can be used to carry out the task maximally. This concept may be more useful than that of a general maximally entangled state in the case of a multipartite system. We illustrate this idea by giving an operational definition of maximally entangled states on the basis of communication tasks of teleportation and superdense coding. We also give examples and a procedure to obtain such TMESs for n-qubit systems.

High Intensity Interval Training for Maximizing Health Outcomes.

Science.gov (United States)

Karlsen, Trine; Aamot, Inger-Lise; Haykowsky, Mark; Rognmo, Øivind

Regular physical activity and exercise training are important actions to improve cardiorespiratory fitness and maintain health throughout life. There is solid evidence that exercise is an effective preventative strategy against at least 25 medical conditions, including cardiovascular disease, stroke, hypertension, colon and breast cancer, and type 2 diabetes. Traditionally, endurance exercise training (ET) to improve health related outcomes has consisted of low- to moderate ET intensity. However, a growing body of evidence suggests that higher exercise intensities may be superior to moderate intensity for maximizing health outcomes. The primary objective of this review is to discuss how aerobic high-intensity interval training (HIIT) as compared to moderate continuous training may maximize outcomes, and to provide practical advices for successful clinical and home-based HIIT. Copyright © 2017. Published by Elsevier Inc.

Risk Presentation Using the Three Dimensions of Likelihood, Severity, and Level of Control

Science.gov (United States)

Watson, Clifford

2010-01-01

Traditional hazard analysis techniques utilize a two-dimensional representation of the results determined by relative likelihood and severity of the residual risk. These matrices present a quick-look at the Likelihood (Y-axis) and Severity (X-axis) of the probable outcome of a hazardous event. A three-dimensional method, described herein, utilizes the traditional X and Y axes, while adding a new, third dimension, shown as the Z-axis, and referred to as the Level of Control. The elements of the Z-axis are modifications of the Hazard Elimination and Control steps (also known as the Hazard Reduction Precedence Sequence). These steps are: 1. Eliminate risk through design. 2. Substitute less risky materials for more hazardous materials. 3. Install safety devices. 4. Install caution and warning devices. 5. Develop administrative controls (to include special procedures and training.) 6. Provide protective clothing and equipment. When added to the two-dimensional models, the level of control adds a visual representation of the risk associated with the hazardous condition, creating a tall-pole for the leastwell-controlled failure while establishing the relative likelihood and severity of all causes and effects for an identified hazard. Computer modeling of the analytical results, using spreadsheets and three-dimensional charting gives a visual confirmation of the relationship between causes and their controls.

Likelihood-ratio-based biometric verification

NARCIS (Netherlands)

Bazen, A.M.; Veldhuis, Raymond N.J.

2002-01-01

This paper presents results on optimal similarity measures for biometric verification based on fixed-length feature vectors. First, we show that the verification of a single user is equivalent to the detection problem, which implies that for single-user verification the likelihood ratio is optimal.

Likelihood Ratio-Based Biometric Verification

NARCIS (Netherlands)

Bazen, A.M.; Veldhuis, Raymond N.J.

The paper presents results on optimal similarity measures for biometric verification based on fixed-length feature vectors. First, we show that the verification of a single user is equivalent to the detection problem, which implies that, for single-user verification, the likelihood ratio is optimal.

Likelihood functions for the analysis of single-molecule binned photon sequences

Energy Technology Data Exchange (ETDEWEB)

Gopich, Irina V., E-mail: irinag@niddk.nih.gov [Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD 20892 (United States)

2012-03-02

Graphical abstract: Folding of a protein with attached fluorescent dyes, the underlying conformational trajectory of interest, and the observed binned photon trajectory. Highlights: Black-Right-Pointing-Pointer A sequence of photon counts can be analyzed using a likelihood function. Black-Right-Pointing-Pointer The exact likelihood function for a two-state kinetic model is provided. Black-Right-Pointing-Pointer Several approximations are considered for an arbitrary kinetic model. Black-Right-Pointing-Pointer Improved likelihood functions are obtained to treat sequences of FRET efficiencies. - Abstract: We consider the analysis of a class of experiments in which the number of photons in consecutive time intervals is recorded. Sequence of photon counts or, alternatively, of FRET efficiencies can be studied using likelihood-based methods. For a kinetic model of the conformational dynamics and state-dependent Poisson photon statistics, the formalism to calculate the exact likelihood that this model describes such sequences of photons or FRET efficiencies is developed. Explicit analytic expressions for the likelihood function for a two-state kinetic model are provided. The important special case when conformational dynamics are so slow that at most a single transition occurs in a time bin is considered. By making a series of approximations, we eventually recover the likelihood function used in hidden Markov models. In this way, not only is insight gained into the range of validity of this procedure, but also an improved likelihood function can be obtained.

FLOUTING MAXIMS IN INDONESIA LAWAK KLUB CONVERSATION

Directory of Open Access Journals (Sweden)

Rahmawati Sukmaningrum

2017-04-01

Full Text Available This study aims to identify the types of maxims flouted in the conversation in famous comedy show, Indonesia Lawak Club. Likewise, it also tries to reveal the speakers‘ intention of flouting the maxim in the conversation during the show. The writers use descriptive qualitative method in conducting this research. The data is taken from the dialogue of Indonesia Lawak club and then analyzed based on Grice‘s cooperative principles. The researchers read the dialogue‘s transcripts, identify the maxims, and interpret the data to find the speakers‘ intention for flouting the maxims in the communication. The results show that there are four types of maxims flouted in the dialogue. Those are maxim of quality (23%, maxim of quantity (11%, maxim of manner (31%, and maxim of relevance (35. Flouting the maxims in the conversations is intended to make the speakers feel uncomfortable with the conversation, show arrogances, show disagreement or agreement, and ridicule other speakers.

Optimization of the Extraction Conditions for Buddleja officinalis Maxim. Using Response Surface Methodology and Exploration of the Optimum Harvest Time

Directory of Open Access Journals (Sweden)

Guoyong Xie

2017-11-01

Full Text Available The Box-Behnken design was used to evaluate the effects of the methanol concentration (60–100%, liquid to solid ratio (20:1 to 40:1 mL/g and extraction time (20–40 min on the yield of 11 constituents from Buddleja officinalis Maxim using ultrasound-assisted extraction. The Derringer’s desirability function approach showed that the modified optimum extraction conditions were: 76% methanol concentration, 33 min extraction time and a 34:1 mL/g solvent to solid ratio. Under these conditions, the experimentally measured yields of the compounds were in good agreement with the predicted values. An accurate and sensitive method was also established using high-performance liquid chromatography with diode-array detection for the simultaneous determination of the 11 compounds in Buddleja officinalis. The newly developed method was used to determine the amounts of bioactive components in Buddleja officinalis during four different growth stages. According to these results, we recommend that the full blossom stage is the best time for harvesting this plant to obtain the highest yield of crude materials.

Optimization of the Extraction Conditions for Buddleja officinalis Maxim. Using Response Surface Methodology and Exploration of the Optimum Harvest Time.

Science.gov (United States)

Xie, Guoyong; Li, Ran; Han, Yu; Zhu, Yan; Wu, Gang; Qin, Minjian

2017-11-01

The Box-Behnken design was used to evaluate the effects of the methanol concentration (60-100%), liquid to solid ratio (20:1 to 40:1 mL/g) and extraction time (20-40 min) on the yield of 11 constituents from Buddleja officinalis Maxim using ultrasound-assisted extraction. The Derringer's desirability function approach showed that the modified optimum extraction conditions were: 76% methanol concentration, 33 min extraction time and a 34:1 mL/g solvent to solid ratio. Under these conditions, the experimentally measured yields of the compounds were in good agreement with the predicted values. An accurate and sensitive method was also established using high-performance liquid chromatography with diode-array detection for the simultaneous determination of the 11 compounds in Buddleja officinalis . The newly developed method was used to determine the amounts of bioactive components in Buddleja officinalis during four different growth stages. According to these results, we recommend that the full blossom stage is the best time for harvesting this plant to obtain the highest yield of crude materials.

Planck 2013 results. XV. CMB power spectra and likelihood

CERN Document Server

Ade, P.A.R.; Armitage-Caplan, C.; Arnaud, M.; Ashdown, M.; Atrio-Barandela, F.; Aumont, J.; Baccigalupi, C.; Banday, A.J.; Barreiro, R.B.; Bartlett, J.G.; Battaner, E.; Benabed, K.; Benoit, A.; Benoit-Levy, A.; Bernard, J.P.; Bersanelli, M.; Bielewicz, P.; Bobin, J.; Bock, J.J.; Bonaldi, A.; Bonavera, L.; Bond, J.R.; Borrill, J.; Bouchet, F.R.; Boulanger, F.; Bridges, M.; Bucher, M.; Burigana, C.; Butler, R.C.; Calabrese, E.; Cardoso, J.F.; Catalano, A.; Challinor, A.; Chamballu, A.; Chiang, L.Y.; Chiang, H.C.; Christensen, P.R.; Church, S.; Clements, D.L.; Colombi, S.; Colombo, L.P.L.; Combet, C.; Couchot, F.; Coulais, A.; Crill, B.P.; Curto, A.; Cuttaia, F.; Danese, L.; Davies, R.D.; Davis, R.J.; de Bernardis, P.; de Rosa, A.; de Zotti, G.; Delabrouille, J.; Delouis, J.M.; Desert, F.X.; Dickinson, C.; Diego, J.M.; Dole, H.; Donzelli, S.; Dore, O.; Douspis, M.; Dunkley, J.; Dupac, X.; Efstathiou, G.; Elsner, F.; Ensslin, T.A.; Eriksen, H.K.; Finelli, F.; Forni, O.; Frailis, M.; Fraisse, A.A.; Franceschi, E.; Gaier, T.C.; Galeotta, S.; Galli, S.; Ganga, K.; Giard, M.; Giardino, G.; Giraud-Heraud, Y.; Gjerlow, E.; Gonzalez-Nuevo, J.; Gorski, K.M.; Gratton, S.; Gregorio, A.; Gruppuso, A.; Gudmundsson, J.E.; Hansen, F.K.; Hanson, D.; Harrison, D.; Helou, G.; Henrot-Versille, S.; Hernandez-Monteagudo, C.; Herranz, D.; Hildebrandt, S.R.; Hivon, E.; Hobson, M.; Holmes, W.A.; Hornstrup, A.; Hovest, W.; Huffenberger, K.M.; Hurier, G.; Jaffe, T.R.; Jaffe, A.H.; Jewell, J.; Jones, W.C.; Juvela, M.; Keihanen, E.; Keskitalo, R.; Kiiveri, K.; Kisner, T.S.; Kneissl, R.; Knoche, J.; Knox, L.; Kunz, M.; Kurki-Suonio, H.; Lagache, G.; Lahteenmaki, A.; Lamarre, J.M.; Lasenby, A.; Lattanzi, M.; Laureijs, R.J.; Lawrence, C.R.; Le Jeune, M.; Leach, S.; Leahy, J.P.; Leonardi, R.; Leon-Tavares, J.; Lesgourgues, J.; Liguori, M.; Lilje, P.B.; Lindholm, V.; Linden-Vornle, M.; Lopez-Caniego, M.; Lubin, P.M.; Macias-Perez, J.F.; Maffei, B.; Maino, D.; Mandolesi, N.; Marinucci, D.; Maris, M.; Marshall, D.J.; Martin, P.G.; Martinez-Gonzalez, E.; Masi, S.; Matarrese, S.; Matthai, F.; Mazzotta, P.; Meinhold, P.R.; Melchiorri, A.; Mendes, L.; Menegoni, E.; Mennella, A.; Migliaccio, M.; Millea, M.; Mitra, S.; Miville-Deschenes, M.A.; Molinari, D.; Moneti, A.; Montier, L.; Morgante, G.; Mortlock, D.; Moss, A.; Munshi, D.; Naselsky, P.; Nati, F.; Natoli, P.; Netterfield, C.B.; Norgaard-Nielsen, H.U.; Noviello, F.; Novikov, D.; Novikov, I.; O'Dwyer, I.J.; Orieux, F.; Osborne, S.; Oxborrow, C.A.; Paci, F.; Pagano, L.; Pajot, F.; Paladini, R.; Paoletti, D.; Partridge, B.; Pasian, F.; Patanchon, G.; Paykari, P.; Perdereau, O.; Perotto, L.; Perrotta, F.; Piacentini, F.; Piat, M.; Pierpaoli, E.; Pietrobon, D.; Plaszczynski, S.; Pointecouteau, E.; Polenta, G.; Ponthieu, N.; Popa, L.; Poutanen, T.; Pratt, G.W.; Prezeau, G.; Prunet, S.; Puget, J.L.; Rachen, J.P.; Rahlin, A.; Rebolo, R.; Reinecke, M.; Remazeilles, M.; Renault, C.; Ricciardi, S.; Riller, T.; Ringeval, C.; Ristorcelli, I.; Rocha, G.; Rosset, C.; Roudier, G.; Rowan-Robinson, M.; Rubino-Martin, J.A.; Rusholme, B.; Sandri, M.; Sanselme, L.; Santos, D.; Savini, G.; Scott, D.; Seiffert, M.D.; Shellard, E.P.S.; Spencer, L.D.; Starck, J.L.; Stolyarov, V.; Stompor, R.; Sudiwala, R.; Sureau, F.; Sutton, D.; Suur-Uski, A.S.; Sygnet, J.F.; Tauber, J.A.; Tavagnacco, D.; Terenzi, L.; Toffolatti, L.; Tomasi, M.; Tristram, M.; Tucci, M.; Tuovinen, J.; Turler, M.; Valenziano, L.; Valiviita, J.; Van Tent, B.; Varis, J.; Vielva, P.; Villa, F.; Vittorio, N.; Wade, L.A.; Wandelt, B.D.; Wehus, I.K.; White, M.; White, S.D.M.; Yvon, D.; Zacchei, A.; Zonca, A.

2014-01-01

We present the Planck likelihood, a complete statistical description of the two-point correlation function of the CMB temperature fluctuations. We use this likelihood to derive the Planck CMB power spectrum over three decades in l, covering 2 = 50, we employ a correlated Gaussian likelihood approximation based on angular cross-spectra derived from the 100, 143 and 217 GHz channels. We validate our likelihood through an extensive suite of consistency tests, and assess the impact of residual foreground and instrumental uncertainties on cosmological parameters. We find good internal agreement among the high-l cross-spectra with residuals of a few uK^2 at l <= 1000. We compare our results with foreground-cleaned CMB maps, and with cross-spectra derived from the 70 GHz Planck map, and find broad agreement in terms of spectrum residuals and cosmological parameters. The best-fit LCDM cosmology is in excellent agreement with preliminary Planck polarisation spectra. The standard LCDM cosmology is well constrained b...

Seasonal species interactions minimize the impact of species turnover on the likelihood of community persistence.

Science.gov (United States)

Saavedra, Serguei; Rohr, Rudolf P; Fortuna, Miguel A; Selva, Nuria; Bascompte, Jordi

2016-04-01

Many of the observed species interactions embedded in ecological communities are not permanent, but are characterized by temporal changes that are observed along with abiotic and biotic variations. While work has been done describing and quantifying these changes, little is known about their consequences for species coexistence. Here, we investigate the extent to which changes of species composition impact the likelihood of persistence of the predator-prey community in the highly seasonal Białowieza Primeval Forest (northeast Poland), and the extent to which seasonal changes of species interactions (predator diet) modulate the expected impact. This likelihood is estimated extending recent developments on the study of structural stability in ecological communities. We find that the observed species turnover strongly varies the likelihood of community persistence between summer and winter. Importantly, we demonstrate that the observed seasonal interaction changes minimize the variation in the likelihood of persistence associated with species turnover across the year. We find that these community dynamics can be explained as the coupling of individual species to their environment by minimizing both the variation in persistence conditions and the interaction changes between seasons. Our results provide a homeostatic explanation for seasonal species interactions and suggest that monitoring the association of interactions changes with the level of variation in community dynamics can provide a good indicator of the response of species to environmental pressures.

VIOLATION OF CONVERSATION MAXIM ON TV ADVERTISEMENTS

Directory of Open Access Journals (Sweden)

Desak Putu Eka Pratiwi

2015-07-01

Full Text Available Maxim is a principle that must be obeyed by all participants textually and interpersonally in order to have a smooth communication process. Conversation maxim is divided into four namely maxim of quality, maxim of quantity, maxim of relevance, and maxim of manner of speaking. Violation of the maxim may occur in a conversation in which the information the speaker has is not delivered well to his speaking partner. Violation of the maxim in a conversation will result in an awkward impression. The example of violation is the given information that is redundant, untrue, irrelevant, or convoluted. Advertisers often deliberately violate the maxim to create unique and controversial advertisements. This study aims to examine the violation of maxims in conversations of TV ads. The source of data in this research is food advertisements aired on TV media. Documentation and observation methods are applied to obtain qualitative data. The theory used in this study is a maxim theory proposed by Grice (1975. The results of the data analysis are presented with informal method. The results of this study show an interesting fact that the violation of maxim in a conversation found in the advertisement exactly makes the advertisements very attractive and have a high value.

Finding Maximal Quasiperiodicities in Strings

DEFF Research Database (Denmark)

Brodal, Gerth Stølting; Pedersen, Christian N. S.

2000-01-01

of length n in time O(n log n) and space O(n). Our algorithm uses the suffix tree as the fundamental data structure combined with efficient methods for merging and performing multiple searches in search trees. Besides finding all maximal quasiperiodic substrings, our algorithm also marks the nodes......Apostolico and Ehrenfeucht defined the notion of a maximal quasiperiodic substring and gave an algorithm that finds all maximal quasiperiodic substrings in a string of length n in time O(n log2 n). In this paper we give an algorithm that finds all maximal quasiperiodic substrings in a string...... in the suffix tree that have a superprimitive path-label....

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

Competitive prices as profit-maximizing cartel prices

OpenAIRE

Houba, H.E.D.; Motchenkova, E.I.; Wen, Q.

2010-01-01

This discussion paper has resulted in a publication in Economics Letters, 114, 39-42. Even under antitrust enforcement, firms may still form a cartel in an infinitely-repeated oligopoly model when the discount factor is sufficiently close to one. We present a linear oligopoly model where the profit-maximizing cartel price converges to the competitive equilibrium price as the discount factor goes to one. We then identify a set of necessary conditions for this seemingly counter-intuitive result.

Non-renormalisation conditions in type II string theory and maximal supergravity

International Nuclear Information System (INIS)

Green, Michael B.; Russo, Jorge G.; Vanhove, Pierre

2007-01-01

This paper considers general features of the derivative expansion of Feynman diagram contributions to the four-graviton scattering amplitude in eleven-dimensional supergravity compactified on a two-torus. These are translated into statements about interactions of the form D 2k R 4 in type II superstring theories, assuming the standard M-theory/string theory duality relationships, which provide powerful constraints on the effective interactions. In the ten-dimensional IIA limit we find that there can be no perturbative contributions beyond k string loops (for k>0). Furthermore, the genus h = k contributions are determined exactly by the one-loop eleven-dimensional supergravity amplitude for all values of k. A plausible interpretation of these observations is that the sum of h-loop Feynman diagrams of maximally extended supergravity is less divergent than might be expected and could be ultraviolet finite in dimensions d<4+6/h - the same bound as for N = 4 Yang-Mills

Non-renormalisation conditions in type II string theory and maximal supergravity

Science.gov (United States)

Green, Michael B.; Russo, Jorge G.; Vanhove, Pierre

2007-02-01

This paper considers general features of the derivative expansion of Feynman diagram contributions to the four-graviton scattering amplitude in eleven-dimensional supergravity compactified on a two-torus. These are translated into statements about interactions of the form D2kR4 in type II superstring theories, assuming the standard M-theory/string theory duality relationships, which provide powerful constraints on the effective interactions. In the ten-dimensional IIA limit we find that there can be no perturbative contributions beyond k string loops (for k>0). Furthermore, the genus h = k contributions are determined exactly by the one-loop eleven-dimensional supergravity amplitude for all values of k. A plausible interpretation of these observations is that the sum of h-loop Feynman diagrams of maximally extended supergravity is less divergent than might be expected and could be ultraviolet finite in dimensions d<4+6/h - the same bound as for N = 4 Yang-Mills.

Shareholder, stakeholder-owner or broad stakeholder maximization

DEFF Research Database (Denmark)

Mygind, Niels

2004-01-01

With reference to the discussion about shareholder versus stakeholder maximization it is argued that the normal type of maximization is in fact stakeholder-owner maxi-mization. This means maximization of the sum of the value of the shares and stake-holder benefits belonging to the dominating...... including the shareholders of a company. Although it may be the ultimate goal for Corporate Social Responsibility to achieve this kind of maximization, broad stakeholder maximization is quite difficult to give a precise definition. There is no one-dimensional measure to add different stakeholder benefits...... not traded on the mar-ket, and therefore there is no possibility for practical application. Broad stakeholder maximization instead in practical applications becomes satisfying certain stakeholder demands, so that the practical application will be stakeholder-owner maximization un-der constraints defined...

On the maximal superalgebras of supersymmetric backgrounds

International Nuclear Information System (INIS)

Figueroa-O'Farrill, Jose; Hackett-Jones, Emily; Moutsopoulos, George; Simon, Joan

2009-01-01

In this paper we give a precise definition of the notion of a maximal superalgebra of certain types of supersymmetric supergravity backgrounds, including the Freund-Rubin backgrounds, and propose a geometric construction extending the well-known construction of its Killing superalgebra. We determine the structure of maximal Lie superalgebras and show that there is a finite number of isomorphism classes, all related via contractions from an orthosymplectic Lie superalgebra. We use the structure theory to show that maximally supersymmetric waves do not possess such a maximal superalgebra, but that the maximally supersymmetric Freund-Rubin backgrounds do. We perform the explicit geometric construction of the maximal superalgebra of AdS 4 X S 7 and find that it is isomorphic to osp(1|32). We propose an algebraic construction of the maximal superalgebra of any background asymptotic to AdS 4 X S 7 and we test this proposal by computing the maximal superalgebra of the M2-brane in its two maximally supersymmetric limits, finding agreement.

The likelihood principle and its proof – a never-ending story…

DEFF Research Database (Denmark)

Jørgensen, Thomas Martini

2015-01-01

An ongoing controversy in philosophy of statistics is the so-called “likelihood principle” essentially stating that all evidence which is obtained from an experiment about an unknown quantity θ is contained in the likelihood function of θ. Common classical statistical methodology, such as the use...... of significance tests, and confidence intervals, depends on the experimental procedure and unrealized events and thus violates the likelihood principle. The likelihood principle was identified by that name and proved in a famous paper by Allan Birnbaum in 1962. However, ever since both the principle itself...... as well as the proof has been highly debated. This presentation will illustrate the debate of both the principle and its proof, from 1962 and up to today. An often-used experiment to illustrate the controversy between classical interpretation and evidential confirmation based on the likelihood principle...

Maximally multipartite entangled states

Science.gov (United States)

Facchi, Paolo; Florio, Giuseppe; Parisi, Giorgio; Pascazio, Saverio

2008-06-01

We introduce the notion of maximally multipartite entangled states of n qubits as a generalization of the bipartite case. These pure states have a bipartite entanglement that does not depend on the bipartition and is maximal for all possible bipartitions. They are solutions of a minimization problem. Examples for small n are investigated, both analytically and numerically.

Maximally Symmetric Composite Higgs Models.

Science.gov (United States)

Csáki, Csaba; Ma, Teng; Shu, Jing

2017-09-29

Maximal symmetry is a novel tool for composite pseudo Goldstone boson Higgs models: it is a remnant of an enhanced global symmetry of the composite fermion sector involving a twisting with the Higgs field. Maximal symmetry has far-reaching consequences: it ensures that the Higgs potential is finite and fully calculable, and also minimizes the tuning. We present a detailed analysis of the maximally symmetric SO(5)/SO(4) model and comment on its observational consequences.

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

Factors Associated with Young Adults’ Pregnancy Likelihood

Science.gov (United States)

Kitsantas, Panagiota; Lindley, Lisa L.; Wu, Huichuan

2014-01-01

OBJECTIVES While progress has been made to reduce adolescent pregnancies in the United States, rates of unplanned pregnancy among young adults (18–29 years) remain high. In this study, we assessed factors associated with perceived likelihood of pregnancy (likelihood of getting pregnant/getting partner pregnant in the next year) among sexually experienced young adults who were not trying to get pregnant and had ever used contraceptives. METHODS We conducted a secondary analysis of 660 young adults, 18–29 years old in the United States, from the cross-sectional National Survey of Reproductive and Contraceptive Knowledge. Logistic regression and classification tree analyses were conducted to generate profiles of young adults most likely to report anticipating a pregnancy in the next year. RESULTS Nearly one-third (32%) of young adults indicated they believed they had at least some likelihood of becoming pregnant in the next year. Young adults who believed that avoiding pregnancy was not very important were most likely to report pregnancy likelihood (odds ratio [OR], 5.21; 95% CI, 2.80–9.69), as were young adults for whom avoiding a pregnancy was important but not satisfied with their current contraceptive method (OR, 3.93; 95% CI, 1.67–9.24), attended religious services frequently (OR, 3.0; 95% CI, 1.52–5.94), were uninsured (OR, 2.63; 95% CI, 1.31–5.26), and were likely to have unprotected sex in the next three months (OR, 1.77; 95% CI, 1.04–3.01). DISCUSSION These results may help guide future research and the development of pregnancy prevention interventions targeting sexually experienced young adults. PMID:25782849

Maximal quantum Fisher information matrix

International Nuclear Information System (INIS)

Chen, Yu; Yuan, Haidong

2017-01-01

We study the existence of the maximal quantum Fisher information matrix in the multi-parameter quantum estimation, which bounds the ultimate precision limit. We show that when the maximal quantum Fisher information matrix exists, it can be directly obtained from the underlying dynamics. Examples are then provided to demonstrate the usefulness of the maximal quantum Fisher information matrix by deriving various trade-off relations in multi-parameter quantum estimation and obtaining the bounds for the scalings of the precision limit. (paper)

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....

Understanding Violations of Gricean Maxims in Preschoolers and Adults

Directory of Open Access Journals (Sweden)

Mako eOkanda

2015-07-01

Full Text Available This study used a revised Conversational Violations Test to examine Gricean maxim violations in 4- to 6-year-old Japanese children and adults. Participants’ understanding of the following maxims was assessed: be informative (first maxim of quantity, avoid redundancy (second maxim of quantity, be truthful (maxim of quality, be relevant (maxim of relation, avoid ambiguity (second maxim of manner, and be polite (maxim of politeness. Sensitivity to violations of Gricean maxims increased with age: 4-year-olds’ understanding of maxims was near chance, 5-year-olds understood some maxims (first maxim of quantity and maxims of quality, relation, and manner, and 6-year-olds and adults understood all maxims. Preschoolers acquired the maxim of relation first and had the greatest difficulty understanding the second maxim of quantity. Children and adults differed in their comprehension of the maxim of politeness. The development of the pragmatic understanding of Gricean maxims and implications for the construction of developmental tasks from early childhood to adulthood are discussed.

Fitting Nonlinear Ordinary Differential Equation Models with Random Effects and Unknown Initial Conditions Using the Stochastic Approximation Expectation-Maximization (SAEM) Algorithm.

Science.gov (United States)

Chow, Sy-Miin; Lu, Zhaohua; Sherwood, Andrew; Zhu, Hongtu

2016-03-01

The past decade has evidenced the increased prevalence of irregularly spaced longitudinal data in social sciences. Clearly lacking, however, are modeling tools that allow researchers to fit dynamic models to irregularly spaced data, particularly data that show nonlinearity and heterogeneity in dynamical structures. We consider the issue of fitting multivariate nonlinear differential equation models with random effects and unknown initial conditions to irregularly spaced data. A stochastic approximation expectation-maximization algorithm is proposed and its performance is evaluated using a benchmark nonlinear dynamical systems model, namely, the Van der Pol oscillator equations. The empirical utility of the proposed technique is illustrated using a set of 24-h ambulatory cardiovascular data from 168 men and women. Pertinent methodological challenges and unresolved issues are discussed.

Statistical modelling of survival data with random effects h-likelihood approach

CERN Document Server

Ha, Il Do; Lee, Youngjo

2017-01-01

This book provides a groundbreaking introduction to the likelihood inference for correlated survival data via the hierarchical (or h-) likelihood in order to obtain the (marginal) likelihood and to address the computational difficulties in inferences and extensions. The approach presented in the book overcomes shortcomings in the traditional likelihood-based methods for clustered survival data such as intractable integration. The text includes technical materials such as derivations and proofs in each chapter, as well as recently developed software programs in R (“frailtyHL”), while the real-world data examples together with an R package, “frailtyHL” in CRAN, provide readers with useful hands-on tools. Reviewing new developments since the introduction of the h-likelihood to survival analysis (methods for interval estimation of the individual frailty and for variable selection of the fixed effects in the general class of frailty models) and guiding future directions, the book is of interest to research...

Downstream-Conditioned Maximum Entropy Method for Exit Boundary Conditions in the Lattice Boltzmann Method

Directory of Open Access Journals (Sweden)

Javier A. Dottori

2015-01-01

Full Text Available A method for modeling outflow boundary conditions in the lattice Boltzmann method (LBM based on the maximization of the local entropy is presented. The maximization procedure is constrained by macroscopic values and downstream components. The method is applied to fully developed boundary conditions of the Navier-Stokes equations in rectangular channels. Comparisons are made with other alternative methods. In addition, the new downstream-conditioned entropy is studied and it was found that there is a correlation with the velocity gradient during the flow development.

Evaluation of Dynamic Coastal Response to Sea-level Rise Modifies Inundation Likelihood

Science.gov (United States)

Lentz, Erika E.; Thieler, E. Robert; Plant, Nathaniel G.; Stippa, Sawyer R.; Horton, Radley M.; Gesch, Dean B.

2016-01-01

Sea-level rise (SLR) poses a range of threats to natural and built environments, making assessments of SLR-induced hazards essential for informed decision making. We develop a probabilistic model that evaluates the likelihood that an area will inundate (flood) or dynamically respond (adapt) to SLR. The broad-area applicability of the approach is demonstrated by producing 30x30m resolution predictions for more than 38,000 sq km of diverse coastal landscape in the northeastern United States. Probabilistic SLR projections, coastal elevation and vertical land movement are used to estimate likely future inundation levels. Then, conditioned on future inundation levels and the current land-cover type, we evaluate the likelihood of dynamic response versus inundation. We find that nearly 70% of this coastal landscape has some capacity to respond dynamically to SLR, and we show that inundation models over-predict land likely to submerge. This approach is well suited to guiding coastal resource management decisions that weigh future SLR impacts and uncertainty against ecological targets and economic constraints.

Maximum Likelihood Estimation and Inference With Examples in R, SAS and ADMB

CERN Document Server

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

Likelihood Analysis of Supersymmetric SU(5) GUTs

CERN Document Server

Bagnaschi, E.

2017-01-01

We perform a likelihood analysis of the constraints from accelerator experiments and astrophysical observations on supersymmetric (SUSY) models with SU(5) boundary conditions on soft SUSY-breaking parameters at the GUT scale. The parameter space of the models studied has 7 parameters: a universal gaugino mass $m_{1/2}$, distinct masses for the scalar partners of matter fermions in five- and ten-dimensional representations of SU(5), $m_5$ and $m_{10}$, and for the $\\mathbf{5}$ and $\\mathbf{\\bar 5}$ Higgs representations $m_{H_u}$ and $m_{H_d}$, a universal trilinear soft SUSY-breaking parameter $A_0$, and the ratio of Higgs vevs $\\tan \\beta$. In addition to previous constraints from direct sparticle searches, low-energy and flavour observables, we incorporate constraints based on preliminary results from 13 TeV LHC searches for jets + MET events and long-lived particles, as well as the latest PandaX-II and LUX searches for direct Dark Matter detection. In addition to previously-identified mechanisms for bringi...

Generalized empirical likelihood methods for analyzing longitudinal data

KAUST Repository

Wang, S.

2010-02-16

Efficient estimation of parameters is a major objective in analyzing longitudinal data. We propose two generalized empirical likelihood based methods that take into consideration within-subject correlations. A nonparametric version of the Wilks theorem for the limiting distributions of the empirical likelihood ratios is derived. It is shown that one of the proposed methods is locally efficient among a class of within-subject variance-covariance matrices. A simulation study is conducted to investigate the finite sample properties of the proposed methods and compare them with the block empirical likelihood method by You et al. (2006) and the normal approximation with a correctly estimated variance-covariance. The results suggest that the proposed methods are generally more efficient than existing methods which ignore the correlation structure, and better in coverage compared to the normal approximation with correctly specified within-subject correlation. An application illustrating our methods and supporting the simulation study results is also presented.

Dimension-independent likelihood-informed MCMC

KAUST Repository

Cui, Tiangang

2015-10-08

Many Bayesian inference problems require exploring the posterior distribution of high-dimensional parameters that represent the discretization of an underlying function. This work introduces a family of Markov chain Monte Carlo (MCMC) samplers that can adapt to the particular structure of a posterior distribution over functions. Two distinct lines of research intersect in the methods developed here. First, we introduce a general class of operator-weighted proposal distributions that are well defined on function space, such that the performance of the resulting MCMC samplers is independent of the discretization of the function. Second, by exploiting local Hessian information and any associated low-dimensional structure in the change from prior to posterior distributions, we develop an inhomogeneous discretization scheme for the Langevin stochastic differential equation that yields operator-weighted proposals adapted to the non-Gaussian structure of the posterior. The resulting dimension-independent and likelihood-informed (DILI) MCMC samplers may be useful for a large class of high-dimensional problems where the target probability measure has a density with respect to a Gaussian reference measure. Two nonlinear inverse problems are used to demonstrate the efficiency of these DILI samplers: an elliptic PDE coefficient inverse problem and path reconstruction in a conditioned diffusion.

Dimension-independent likelihood-informed MCMC

KAUST Repository

Cui, Tiangang; Law, Kody; Marzouk, Youssef M.

2015-01-01

Many Bayesian inference problems require exploring the posterior distribution of high-dimensional parameters that represent the discretization of an underlying function. This work introduces a family of Markov chain Monte Carlo (MCMC) samplers that can adapt to the particular structure of a posterior distribution over functions. Two distinct lines of research intersect in the methods developed here. First, we introduce a general class of operator-weighted proposal distributions that are well defined on function space, such that the performance of the resulting MCMC samplers is independent of the discretization of the function. Second, by exploiting local Hessian information and any associated low-dimensional structure in the change from prior to posterior distributions, we develop an inhomogeneous discretization scheme for the Langevin stochastic differential equation that yields operator-weighted proposals adapted to the non-Gaussian structure of the posterior. The resulting dimension-independent and likelihood-informed (DILI) MCMC samplers may be useful for a large class of high-dimensional problems where the target probability measure has a density with respect to a Gaussian reference measure. Two nonlinear inverse problems are used to demonstrate the efficiency of these DILI samplers: an elliptic PDE coefficient inverse problem and path reconstruction in a conditioned diffusion.

Potential benefits of maximal exercise just prior to return from weightlessness

Science.gov (United States)

Convertino, Victor A.

1987-01-01

The purpose of this study was to determine whether performance of a single maximal bout of exercise during weightlessness within hours of return to earth would enhance recovery of aerobic fitness and physical work capacities under a 1G environment. Ten healthy men were subjected to a 10-d bedrest period in the 6-deg headdown position. A graded maximal supine cycle ergometer test was performed before and at the end of bedrest to simulate exercise during weightlessness. Following 3 h of resumption of the upright posture, a second maximal exercise test was performed on a treadmill to measure work capacity under conditions of 1G. Compared to before bedrest, peak oxygen consumption, V(O2), decreased by 8.7 percent and peak heart rate (HR) increased by 5.6 percent in the supine cycle test at the end of bedrest. However, there were no significant changes in peak V(O2) and peak HR in the upright treadmill test following bedrest. These data suggest that one bout of maximal leg exercise prior to return from 10 d of weightlessness may be adequate to restore preflight aerobic fitness and physical work capacity.

Clarification of the use of chi-square and likelihood functions in fits to histograms

International Nuclear Information System (INIS)

Baker, S.; Cousins, R.D.

1984-01-01

We consider the problem of fitting curves to histograms in which the data obey multinomial or Poisson statistics. Techniques commonly used by physicists are examined in light of standard results found in the statistics literature. We review the relationship between multinomial and Poisson distributions, and clarify a sufficient condition for equality of the area under the fitted curve and the number of events on the histogram. Following the statisticians, we use the likelihood ratio test to construct a general Z 2 statistic, Zsub(lambda) 2 , which yields parameter and error estimates identical to those of the method of maximum likelihood. The Zsub(lambda) 2 statistic is further useful for testing goodness-of-fit since the value of its minimum asymptotically obeys a classical chi-square distribution. One should be aware, however, of the potential for statistical bias, especially when the number of events is small. (orig.)

On the likelihood function of Gaussian max-stable processes

KAUST Repository

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

KAUST Repository

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.

Sampling variability in forensic likelihood-ratio computation: A simulation study

NARCIS (Netherlands)

Ali, Tauseef; Spreeuwers, Lieuwe Jan; Veldhuis, Raymond N.J.; Meuwly, Didier

2015-01-01

Recently, in the forensic biometric community, there is a growing interest to compute a metric called “likelihood- ratio‿ when a pair of biometric specimens is compared using a biometric recognition system. Generally, a biomet- ric recognition system outputs a score and therefore a likelihood-ratio

Maximum likelihood estimation of finite mixture model for economic data

Science.gov (United States)

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.

Assessing Compatibility of Direct Detection Data: Halo-Independent Global Likelihood Analyses

CERN Document Server

Gelmini, Graciela B.

2016-10-18

We present two different halo-independent methods utilizing a global maximum likelihood that can assess the compatibility of dark matter direct detection data given a particular dark matter model. The global likelihood we use is comprised of at least one extended likelihood and an arbitrary number of Poisson or Gaussian likelihoods. In the first method we find the global best fit halo function and construct a two sided pointwise confidence band, which can then be compared with those derived from the extended likelihood alone to assess the joint compatibility of the data. In the second method we define a "constrained parameter goodness-of-fit" test statistic, whose $p$-value we then use to define a "plausibility region" (e.g. where $p \\geq 10\\%$). For any halo function not entirely contained within the plausibility region, the level of compatibility of the data is very low (e.g. $p < 10 \\%$). As an example we apply these methods to CDMS-II-Si and SuperCDMS data, assuming dark matter particles with elastic s...

A short proof that phylogenetic tree reconstruction by maximum likelihood is hard.

Science.gov (United States)

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

OpenAIRE

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 maximal massive 3D supergravity

OpenAIRE

Bergshoeff , Eric A; Hohm , Olaf; Rosseel , Jan; Townsend , Paul K

2010-01-01

ABSTRACT We construct, at the linearized level, the three-dimensional (3D) N = 4 supersymmetric " general massive supergravity " and the maximally supersymmetric N = 8 " new massive supergravity ". We also construct the maximally supersymmetric linearized N = 7 topologically massive supergravity, although we expect N = 6 to be maximal at the non-linear level. (Bergshoeff, Eric A) (Hohm, Olaf) (Rosseel, Jan) P.K.Townsend@da...

Growth-Maximizing Public Debt under Changing Demographics

DEFF Research Database (Denmark)

Bokan, Nikola; Hougaard Jensen, Svend E.; Hallett, Andrew Hughes

2016-01-01

This paper develops an overlapping-generations model to study the growth-maximizing level of public debt under conditions of demograhic change. It is shown that the optimal debt level depends on a positive marginal productivity of public capital. In general, it also depends on the demographic par...... will have to adjust its fiscal plans to accommodate those changes, most likely downward, if growth is to be preserved. An advantage of this model is that it allows us to determine in advance the way in which fiscal policies need to adjust as demographic parameters change....

Inclusive fitness maximization: An axiomatic approach.

Science.gov (United States)

Okasha, Samir; Weymark, John A; Bossert, Walter

2014-06-07

Kin selection theorists argue that evolution in social contexts will lead organisms to behave as if maximizing their inclusive, as opposed to personal, fitness. The inclusive fitness concept allows biologists to treat organisms as akin to rational agents seeking to maximize a utility function. Here we develop this idea and place it on a firm footing by employing a standard decision-theoretic methodology. We show how the principle of inclusive fitness maximization and a related principle of quasi-inclusive fitness maximization can be derived from axioms on an individual׳s 'as if preferences' (binary choices) for the case in which phenotypic effects are additive. Our results help integrate evolutionary theory and rational choice theory, help draw out the behavioural implications of inclusive fitness maximization, and point to a possible way in which evolution could lead organisms to implement it. Copyright © 2014 Elsevier Ltd. All rights reserved.

Moral Identity Predicts Doping Likelihood via Moral Disengagement and Anticipated Guilt.

Science.gov (United States)

Kavussanu, Maria; Ring, Christopher

2017-08-01

In this study, we integrated elements of social cognitive theory of moral thought and action and the social cognitive model of moral identity to better understand doping likelihood in athletes. Participants (N = 398) recruited from a variety of team sports completed measures of moral identity, moral disengagement, anticipated guilt, and doping likelihood. Moral identity predicted doping likelihood indirectly via moral disengagement and anticipated guilt. Anticipated guilt about potential doping mediated the relationship between moral disengagement and doping likelihood. Our findings provide novel evidence to suggest that athletes, who feel that being a moral person is central to their self-concept, are less likely to use banned substances due to their lower tendency to morally disengage and the more intense feelings of guilt they expect to experience for using banned substances.

A Lyapunov based approach to energy maximization in renewable energy technologies

Science.gov (United States)

Iyasere, Erhun

This dissertation describes the design and implementation of Lyapunov-based control strategies for the maximization of the power captured by renewable energy harnessing technologies such as (i) a variable speed, variable pitch wind turbine, (ii) a variable speed wind turbine coupled to a doubly fed induction generator, and (iii) a solar power generating system charging a constant voltage battery. First, a torque control strategy is presented to maximize wind energy captured in variable speed, variable pitch wind turbines at low to medium wind speeds. The proposed strategy applies control torque to the wind turbine pitch and rotor subsystems to simultaneously control the blade pitch and tip speed ratio, via the rotor angular speed, to an optimum point at which the capture efficiency is maximum. The control method allows for aerodynamic rotor power maximization without exact knowledge of the wind turbine model. A series of numerical results show that the wind turbine can be controlled to achieve maximum energy capture. Next, a control strategy is proposed to maximize the wind energy captured in a variable speed wind turbine, with an internal induction generator, at low to medium wind speeds. The proposed strategy controls the tip speed ratio, via the rotor angular speed, to an optimum point at which the efficiency constant (or power coefficient) is maximal for a particular blade pitch angle and wind speed by using the generator rotor voltage as a control input. This control method allows for aerodynamic rotor power maximization without exact wind turbine model knowledge. Representative numerical results demonstrate that the wind turbine can be controlled to achieve near maximum energy capture. Finally, a power system consisting of a photovoltaic (PV) array panel, dc-to-dc switching converter, charging a battery is considered wherein the environmental conditions are time-varying. A backstepping PWM controller is developed to maximize the power of the solar generating

Maximum likelihood of phylogenetic networks.

Science.gov (United States)

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

Climate reconstruction analysis using coexistence likelihood estimation (CRACLE): a method for the estimation of climate using vegetation.

Science.gov (United States)

Harbert, Robert S; Nixon, Kevin C

2015-08-01

• Plant distributions have long been understood to be correlated with the environmental conditions to which species are adapted. Climate is one of the major components driving species distributions. Therefore, it is expected that the plants coexisting in a community are reflective of the local environment, particularly climate.• Presented here is a method for the estimation of climate from local plant species coexistence data. The method, Climate Reconstruction Analysis using Coexistence Likelihood Estimation (CRACLE), is a likelihood-based method that employs specimen collection data at a global scale for the inference of species climate tolerance. CRACLE calculates the maximum joint likelihood of coexistence given individual species climate tolerance characterization to estimate the expected climate.• Plant distribution data for more than 4000 species were used to show that this method accurately infers expected climate profiles for 165 sites with diverse climatic conditions. Estimates differ from the WorldClim global climate model by less than 1.5°C on average for mean annual temperature and less than ∼250 mm for mean annual precipitation. This is a significant improvement upon other plant-based climate-proxy methods.• CRACLE validates long hypothesized interactions between climate and local associations of plant species. Furthermore, CRACLE successfully estimates climate that is consistent with the widely used WorldClim model and therefore may be applied to the quantitative estimation of paleoclimate in future studies. © 2015 Botanical Society of America, Inc.

Risk Assessment Using the Three Dimensions of Probability (Likelihood), Severity, and Level of Control

Science.gov (United States)

Watson, Clifford C.

2011-01-01

Traditional hazard analysis techniques utilize a two-dimensional representation of the results determined by relative likelihood and severity of the residual risk. These matrices present a quick-look at the Likelihood (Y-axis) and Severity (X-axis) of the probable outcome of a hazardous event. A three-dimensional method, described herein, utilizes the traditional X and Y axes, while adding a new, third dimension, shown as the Z-axis, and referred to as the Level of Control. The elements of the Z-axis are modifications of the Hazard Elimination and Control steps (also known as the Hazard Reduction Precedence Sequence). These steps are: 1. Eliminate risk through design. 2. Substitute less risky materials for more hazardous materials. 3. Install safety devices. 4. Install caution and warning devices. 5. Develop administrative controls (to include special procedures and training.) 6. Provide protective clothing and equipment. When added to the two-dimensional models, the level of control adds a visual representation of the risk associated with the hazardous condition, creating a tall-pole for the least-well-controlled failure while establishing the relative likelihood and severity of all causes and effects for an identified hazard. Computer modeling of the analytical results, using spreadsheets and three-dimensional charting gives a visual confirmation of the relationship between causes and their controls.

Maximal Entanglement in High Energy Physics

Directory of Open Access Journals (Sweden)

Alba Cervera-Lierta, José I. Latorre, Juan Rojo, Luca Rottoli

2017-11-01

Full Text Available We analyze how maximal entanglement is generated at the fundamental level in QED by studying correlations between helicity states in tree-level scattering processes at high energy. We demonstrate that two mechanisms for the generation of maximal entanglement are at work: i $s$-channel processes where the virtual photon carries equal overlaps of the helicities of the final state particles, and ii the indistinguishable superposition between $t$- and $u$-channels. We then study whether requiring maximal entanglement constrains the coupling structure of QED and the weak interactions. In the case of photon-electron interactions unconstrained by gauge symmetry, we show how this requirement allows reproducing QED. For $Z$-mediated weak scattering, the maximal entanglement principle leads to non-trivial predictions for the value of the weak mixing angle $\\theta_W$. Our results are a first step towards understanding the connections between maximal entanglement and the fundamental symmetries of high-energy physics.

Predictors of Self-Reported Likelihood of Working with Older Adults

Science.gov (United States)

Eshbaugh, Elaine M.; Gross, Patricia E.; Satrom, Tatum

2010-01-01

This study examined the self-reported likelihood of working with older adults in a future career among 237 college undergraduates at a midsized Midwestern university. Although aging anxiety was not significantly related to likelihood of working with older adults, those students who had a greater level of death anxiety were less likely than other…

Anticipating cognitive effort: roles of perceived error-likelihood and time demands.

Science.gov (United States)

Dunn, Timothy L; Inzlicht, Michael; Risko, Evan F

2017-11-13

Why are some actions evaluated as effortful? In the present set of experiments we address this question by examining individuals' perception of effort when faced with a trade-off between two putative cognitive costs: how much time a task takes vs. how error-prone it is. Specifically, we were interested in whether individuals anticipate engaging in a small amount of hard work (i.e., low time requirement, but high error-likelihood) vs. a large amount of easy work (i.e., high time requirement, but low error-likelihood) as being more effortful. In between-subject designs, Experiments 1 through 3 demonstrated that individuals anticipate options that are high in perceived error-likelihood (yet less time consuming) as more effortful than options that are perceived to be more time consuming (yet low in error-likelihood). Further, when asked to evaluate which of the two tasks was (a) more effortful, (b) more error-prone, and (c) more time consuming, effort-based and error-based choices closely tracked one another, but this was not the case for time-based choices. Utilizing a within-subject design, Experiment 4 demonstrated overall similar pattern of judgments as Experiments 1 through 3. However, both judgments of error-likelihood and time demand similarly predicted effort judgments. Results are discussed within the context of extant accounts of cognitive control, with considerations of how error-likelihood and time demands may independently and conjunctively factor into judgments of cognitive effort.

An ethical justification of profit maximization

DEFF Research Database (Denmark)

Koch, Carsten Allan

2010-01-01

In much of the literature on business ethics and corporate social responsibility, it is more or less taken for granted that attempts to maximize profits are inherently unethical. The purpose of this paper is to investigate whether an ethical argument can be given in support of profit maximizing...... behaviour. It is argued that some form of consequential ethics must be applied, and that both profit seeking and profit maximization can be defended from a rule-consequential point of view. It is noted, however, that the result does not apply unconditionally, but requires that certain form of profit (and...... utility) maximizing actions are ruled out, e.g., by behavioural norms or formal institutions....

LOAD THAT MAXIMIZES POWER OUTPUT IN COUNTERMOVEMENT JUMP

Directory of Open Access Journals (Sweden)

Pedro Jimenez-Reyes

2016-02-01

Full Text Available ABSTRACT Introduction: One of the main problems faced by strength and conditioning coaches is the issue of how to objectively quantify and monitor the actual training load undertaken by athletes in order to maximize performance. It is well known that performance of explosive sports activities is largely determined by mechanical power. Objective: This study analysed the height at which maximal power output is generated and the corresponding load with which is achieved in a group of male-trained track and field athletes in the test of countermovement jump (CMJ with extra loads (CMJEL. Methods: Fifty national level male athletes in sprinting and jumping performed a CMJ test with increasing loads up to a height of 16 cm. The relative load that maximized the mechanical power output (Pmax was determined using a force platform and lineal encoder synchronization and estimating the power by peak power, average power and flight time in CMJ. Results: The load at which the power output no longer existed was at a height of 19.9 ± 2.35, referring to a 99.1 ± 1% of the maximum power output. The load that maximizes power output in all cases has been the load with which an athlete jump a height of approximately 20 cm. Conclusion: These results highlight the importance of considering the height achieved in CMJ with extra load instead of power because maximum power is always attained with the same height. We advise for the preferential use of the height achieved in CMJEL test, since it seems to be a valid indicative of an individual's actual neuromuscular potential providing a valid information for coaches and trainers when assessing the performance status of our athletes and to quantify and monitor training loads, measuring only the height of the jump in the exercise of CMJEL.

An Expectation Maximization Algorithm to Model Failure Times by Continuous-Time Markov Chains

Directory of Open Access Journals (Sweden)

Qihong Duan

2010-01-01

Full Text Available In many applications, the failure rate function may present a bathtub shape curve. In this paper, an expectation maximization algorithm is proposed to construct a suitable continuous-time Markov chain which models the failure time data by the first time reaching the absorbing state. Assume that a system is described by methods of supplementary variables, the device of stage, and so on. Given a data set, the maximum likelihood estimators of the initial distribution and the infinitesimal transition rates of the Markov chain can be obtained by our novel algorithm. Suppose that there are m transient states in the system and that there are n failure time data. The devised algorithm only needs to compute the exponential of m×m upper triangular matrices for O(nm2 times in each iteration. Finally, the algorithm is applied to two real data sets, which indicates the practicality and efficiency of our algorithm.

Profile-likelihood Confidence Intervals in Item Response Theory Models.

Science.gov (United States)

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.

Supplementary Material for: High-Order Composite Likelihood Inference for Max-Stable Distributions and Processes

KAUST Repository

Castruccio, Stefano; Huser, Raphaë l; Genton, Marc G.

2016-01-01

In multivariate or spatial extremes, inference for max-stable processes observed at a large collection of points is a very challenging problem and current approaches typically rely on less expensive composite likelihoods constructed from small subsets of data. In this work, we explore the limits of modern state-of-the-art computational facilities to perform full likelihood inference and to efficiently evaluate high-order composite likelihoods. With extensive simulations, we assess the loss of information of composite likelihood estimators with respect to a full likelihood approach for some widely used multivariate or spatial extreme models, we discuss how to choose composite likelihood truncation to improve the efficiency, and we also provide recommendations for practitioners. This article has supplementary material online.

Exclusion probabilities and likelihood ratios with applications to mixtures.

Science.gov (United States)

Slooten, Klaas-Jan; Egeland, Thore

2016-01-01

The statistical evidence obtained from mixed DNA profiles can be summarised in several ways in forensic casework including the likelihood ratio (LR) and the Random Man Not Excluded (RMNE) probability. The literature has seen a discussion of the advantages and disadvantages of likelihood ratios and exclusion probabilities, and part of our aim is to bring some clarification to this debate. In a previous paper, we proved that there is a general mathematical relationship between these statistics: RMNE can be expressed as a certain average of the LR, implying that the expected value of the LR, when applied to an actual contributor to the mixture, is at least equal to the inverse of the RMNE. While the mentioned paper presented applications for kinship problems, the current paper demonstrates the relevance for mixture cases, and for this purpose, we prove some new general properties. We also demonstrate how to use the distribution of the likelihood ratio for donors of a mixture, to obtain estimates for exceedance probabilities of the LR for non-donors, of which the RMNE is a special case corresponding to L R>0. In order to derive these results, we need to view the likelihood ratio as a random variable. In this paper, we describe how such a randomization can be achieved. The RMNE is usually invoked only for mixtures without dropout. In mixtures, artefacts like dropout and drop-in are commonly encountered and we address this situation too, illustrating our results with a basic but widely implemented model, a so-called binary model. The precise definitions, modelling and interpretation of the required concepts of dropout and drop-in are not entirely obvious, and we attempt to clarify them here in a general likelihood framework for a binary model.

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

Inclusive Fitness Maximization:An Axiomatic Approach

OpenAIRE

Okasha, Samir; Weymark, John; Bossert, Walter

2014-01-01

Kin selection theorists argue that evolution in social contexts will lead organisms to behave as if maximizing their inclusive, as opposed to personal, fitness. The inclusive fitness concept allows biologists to treat organisms as akin to rational agents seeking to maximize a utility function. Here we develop this idea and place it on a firm footing by employing a standard decision-theoretic methodology. We show how the principle of inclusive fitness maximization and a related principle of qu...

Sampling of systematic errors to estimate likelihood weights in nuclear data uncertainty propagation

International Nuclear Information System (INIS)

Helgesson, P.; Sjöstrand, H.; Koning, A.J.; Rydén, J.; Rochman, D.; Alhassan, E.; Pomp, S.

2016-01-01

In methodologies for nuclear data (ND) uncertainty assessment and propagation based on random sampling, likelihood weights can be used to infer experimental information into the distributions for the ND. As the included number of correlated experimental points grows large, the computational time for the matrix inversion involved in obtaining the likelihood can become a practical problem. There are also other problems related to the conventional computation of the likelihood, e.g., the assumption that all experimental uncertainties are Gaussian. In this study, a way to estimate the likelihood which avoids matrix inversion is investigated; instead, the experimental correlations are included by sampling of systematic errors. It is shown that the model underlying the sampling methodology (using univariate normal distributions for random and systematic errors) implies a multivariate Gaussian for the experimental points (i.e., the conventional model). It is also shown that the likelihood estimates obtained through sampling of systematic errors approach the likelihood obtained with matrix inversion as the sample size for the systematic errors grows large. In studied practical cases, it is seen that the estimates for the likelihood weights converge impractically slowly with the sample size, compared to matrix inversion. The computational time is estimated to be greater than for matrix inversion in cases with more experimental points, too. Hence, the sampling of systematic errors has little potential to compete with matrix inversion in cases where the latter is applicable. Nevertheless, the underlying model and the likelihood estimates can be easier to intuitively interpret than the conventional model and the likelihood function involving the inverted covariance matrix. Therefore, this work can both have pedagogical value and be used to help motivating the conventional assumption of a multivariate Gaussian for experimental data. The sampling of systematic errors could also

Approximate maximum likelihood estimation for population genetic inference.

Science.gov (United States)

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.

Influence of variable resistance loading on subsequent free weight maximal back squat performance.

Science.gov (United States)

Mina, Minas A; Blazevich, Anthony J; Giakas, Giannis; Kay, Anthony D

2014-10-01

The purpose of the study was to determine the potentiating effects of variable resistance (VR) exercise during a warm-up on subsequent free-weight resistance (FWR) maximal squat performance. In the first session, 16 recreationally active men (age = 26.0 ± 7.8 years; height = 1.7 ± 0.2 m; mass = 82.6 ± 12.7 kg) were familiarized with the experimental protocols and tested for 1 repetition maximum (1RM) squat lift. The subjects then visited the laboratory on 2 further occasions under either control or experimental conditions. During these conditions, 2 sets of 3 repetitions of either FWR (control) or VR (experimental) squat lifts at 85% of 1RM were performed; during the experimental condition, 35% of the load was generated from band tension. After a 5-minute rest, 1RM, 3D knee joint kinematics, and vastus medialis, vastus lateralis, rectus femoris, and semitendinosus electromyogram (EMG) signals were recorded simultaneously. No subject increased 1RM after FWR, however, 13 of 16 (81%) subjects increased 1RM after VR (mean = 7.7%; p 0.05) or EMG amplitudes (mean = 5.9%; p > 0.05) occurred. Preconditioning using VR significantly increased 1RM without detectable changes in knee extensor muscle activity or knee flexion angle, although eccentric and concentric velocities were reduced. Thus, VR seems to potentiate the neuromuscular system to enhance subsequent maximal lifting performance. Athletes could thus use VR during warm-up routines to maximize squat performance.

Likelihood ratio decisions in memory: three implied regularities.

Science.gov (United States)

Glanzer, Murray; Hilford, Andrew; Maloney, Laurence T

2009-06-01

We analyze four general signal detection models for recognition memory that differ in their distributional assumptions. Our analyses show that a basic assumption of signal detection theory, the likelihood ratio decision axis, implies three regularities in recognition memory: (1) the mirror effect, (2) the variance effect, and (3) the z-ROC length effect. For each model, we present the equations that produce the three regularities and show, in computed examples, how they do so. We then show that the regularities appear in data from a range of recognition studies. The analyses and data in our study support the following generalization: Individuals make efficient recognition decisions on the basis of likelihood ratios.

Asymptotic Likelihood Distribution for Correlated & Constrained Systems

CERN Document Server

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.

Comparison of likelihood testing procedures for parallel systems with covariances

International Nuclear Information System (INIS)

Ayman Baklizi; Isa Daud; Noor Akma Ibrahim

1998-01-01

In this paper we considered investigating and comparing the behavior of the likelihood ratio, the Rao's and the Wald's statistics for testing hypotheses on the parameters of the simple linear regression model based on parallel systems with covariances. These statistics are asymptotically equivalent (Barndorff-Nielsen and Cox, 1994). However, their relative performances in finite samples are generally known. A Monte Carlo experiment is conducted to stimulate the sizes and the powers of these statistics for complete samples and in the presence of time censoring. Comparisons of the statistics are made according to the attainment of assumed size of the test and their powers at various points in the parameter space. The results show that the likelihood ratio statistics appears to have the best performance in terms of the attainment of the assumed size of the test. Power comparisons show that the Rao statistic has some advantage over the Wald statistic in almost all of the space of alternatives while likelihood ratio statistic occupies either the first or the last position in term of power. Overall, the likelihood ratio statistic appears to be more appropriate to the model under study, especially for small sample sizes

Finite mixture model: A maximum likelihood estimation approach on time series data

Science.gov (United States)

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.

Expert elicitation on ultrafine particles: likelihood of health effects and causal pathways

Directory of Open Access Journals (Sweden)

Brunekreef Bert

2009-07-01

Full Text Available Abstract Background Exposure to fine ambient particulate matter (PM has consistently been associated with increased morbidity and mortality. The relationship between exposure to ultrafine particles (UFP and health effects is less firmly established. If UFP cause health effects independently from coarser fractions, this could affect health impact assessment of air pollution, which would possibly lead to alternative policy options to be considered to reduce the disease burden of PM. Therefore, we organized an expert elicitation workshop to assess the evidence for a causal relationship between exposure to UFP and health endpoints. Methods An expert elicitation on the health effects of ambient ultrafine particle exposure was carried out, focusing on: 1 the likelihood of causal relationships with key health endpoints, and 2 the likelihood of potential causal pathways for cardiac events. Based on a systematic peer-nomination procedure, fourteen European experts (epidemiologists, toxicologists and clinicians were selected, of whom twelve attended. They were provided with a briefing book containing key literature. After a group discussion, individual expert judgments in the form of ratings of the likelihood of causal relationships and pathways were obtained using a confidence scheme adapted from the one used by the Intergovernmental Panel on Climate Change. Results The likelihood of an independent causal relationship between increased short-term UFP exposure and increased all-cause mortality, hospital admissions for cardiovascular and respiratory diseases, aggravation of asthma symptoms and lung function decrements was rated medium to high by most experts. The likelihood for long-term UFP exposure to be causally related to all cause mortality, cardiovascular and respiratory morbidity and lung cancer was rated slightly lower, mostly medium. The experts rated the likelihood of each of the six identified possible causal pathways separately. Out of these

Insulin resistance and maximal oxygen uptake

DEFF Research Database (Denmark)

Seibaek, Marie; Vestergaard, Henrik; Burchardt, Hans

2003-01-01

BACKGROUND: Type 2 diabetes, coronary atherosclerosis, and physical fitness all correlate with insulin resistance, but the relative importance of each component is unknown. HYPOTHESIS: This study was undertaken to determine the relationship between insulin resistance, maximal oxygen uptake......, and the presence of either diabetes or ischemic heart disease. METHODS: The study population comprised 33 patients with and without diabetes and ischemic heart disease. Insulin resistance was measured by a hyperinsulinemic euglycemic clamp; maximal oxygen uptake was measured during a bicycle exercise test. RESULTS......: There was a strong correlation between maximal oxygen uptake and insulin-stimulated glucose uptake (r = 0.7, p = 0.001), and maximal oxygen uptake was the only factor of importance for determining insulin sensitivity in a model, which also included the presence of diabetes and ischemic heart disease. CONCLUSION...

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

POLITENESS MAXIM OF MAIN CHARACTER IN SECRET FORGIVEN

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Sang Ayu Isnu Maharani

2017-06-01

Full Text Available Maxim of Politeness is an interesting subject to be discussed, since politeness has been criticized from our childhood. We are obliques to be polite to anyone either in speaking or in acting. Somehow we are manage to show politeness in our spoken expression though our intention might be not so polite. For example we must appriciate others opinion although we feel objection toward the opinion. In this article the analysis of politeness is based on maxim proposes by Leech. He proposed six types of politeness maxim. The discussion shows that the main character (Kristen and Kami use all types of maxim in their conversation. The most commonly used are approbation maxim and agreement maxim

Reducing the likelihood of future human activities that could affect geologic high-level waste repositories

International Nuclear Information System (INIS)

1984-05-01

The disposal of radioactive wastes in deep geologic formations provides a means of isolating the waste from people until the radioactivity has decayed to safe levels. However, isolating people from the wastes is a different problem, since we do not know what the future condition of society will be. The Human Interference Task Force was convened by the US Department of Energy to determine whether reasonable means exist (or could be developed) to reduce the likelihood of future human unintentionally intruding on radioactive waste isolation systems. The task force concluded that significant reductions in the likelihood of human interference could be achieved, for perhaps thousands of years into the future, if appropriate steps are taken to communicate the existence of the repository. Consequently, for two years the task force directed most of its study toward the area of long-term communication. Methods are discussed for achieving long-term communication by using permanent markers and widely disseminated records, with various steps taken to provide multiple levels of protection against loss, destruction, and major language/societal changes. Also developed is the concept of a universal symbol to denote Caution - Biohazardous Waste Buried Here. If used for the thousands of non-radioactive biohazardous waste sites in this country alone, a symbol could transcend generations and language changes, thereby vastly improving the likelihood of successful isolation of all buried biohazardous wastes

Robust Multi-Frame Adaptive Optics Image Restoration Algorithm Using Maximum Likelihood Estimation with Poisson Statistics

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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.

Reducing the likelihood of future human activities that could affect geologic high-level waste repositories

Energy Technology Data Exchange (ETDEWEB)

1984-05-01

The disposal of radioactive wastes in deep geologic formations provides a means of isolating the waste from people until the radioactivity has decayed to safe levels. However, isolating people from the wastes is a different problem, since we do not know what the future condition of society will be. The Human Interference Task Force was convened by the US Department of Energy to determine whether reasonable means exist (or could be developed) to reduce the likelihood of future human unintentionally intruding on radioactive waste isolation systems. The task force concluded that significant reductions in the likelihood of human interference could be achieved, for perhaps thousands of years into the future, if appropriate steps are taken to communicate the existence of the repository. Consequently, for two years the task force directed most of its study toward the area of long-term communication. Methods are discussed for achieving long-term communication by using permanent markers and widely disseminated records, with various steps taken to provide multiple levels of protection against loss, destruction, and major language/societal changes. Also developed is the concept of a universal symbol to denote Caution - Biohazardous Waste Buried Here. If used for the thousands of non-radioactive biohazardous waste sites in this country alone, a symbol could transcend generations and language changes, thereby vastly improving the likelihood of successful isolation of all buried biohazardous wastes.

Maximizing Macromolecule Crystal Size for Neutron Diffraction Experiments

Science.gov (United States)

Judge, R. A.; Kephart, R.; Leardi, R.; Myles, D. A.; Snell, E. H.; vanderWoerd, M.; Curreri, Peter A. (Technical Monitor)

2002-01-01

A challenge in neutron diffraction experiments is growing large (greater than 1 cu mm) macromolecule crystals. In taking up this challenge we have used statistical experiment design techniques to quickly identify crystallization conditions under which the largest crystals grow. These techniques provide the maximum information for minimal experimental effort, allowing optimal screening of crystallization variables in a simple experimental matrix, using the minimum amount of sample. Analysis of the results quickly tells the investigator what conditions are the most important for the crystallization. These can then be used to maximize the crystallization results in terms of reducing crystal numbers and providing large crystals of suitable habit. We have used these techniques to grow large crystals of Glucose isomerase. Glucose isomerase is an industrial enzyme used extensively in the food industry for the conversion of glucose to fructose. The aim of this study is the elucidation of the enzymatic mechanism at the molecular level. The accurate determination of hydrogen positions, which is critical for this, is a requirement that neutron diffraction is uniquely suited for. Preliminary neutron diffraction experiments with these crystals conducted at the Institute Laue-Langevin (Grenoble, France) reveal diffraction to beyond 2.5 angstrom. Macromolecular crystal growth is a process involving many parameters, and statistical experimental design is naturally suited to this field. These techniques are sample independent and provide an experimental strategy to maximize crystal volume and habit for neutron diffraction studies.

Maximization of fructose esters synthesis by response surface methodology.

Science.gov (United States)

Neta, Nair Sampaio; Peres, António M; Teixeira, José A; Rodrigues, Ligia R

2011-07-01

Enzymatic synthesis of fructose fatty acid ester was performed in organic solvent media, using a purified lipase from Candida antartica B immobilized in acrylic resin. Response surface methodology with a central composite rotatable design based on five levels was implemented to optimize three experimental operating conditions (temperature, agitation and reaction time). A statistical significant cubic model was established. Temperature and reaction time were found to be the most significant parameters. The optimum operational conditions for maximizing the synthesis of fructose esters were 57.1°C, 100 rpm and 37.8 h. The model was validated in the identified optimal conditions to check its adequacy and accuracy, and an experimental esterification percentage of 88.4% (±0.3%) was obtained. These results showed that an improvement of the enzymatic synthesis of fructose esters was obtained under the optimized conditions. Copyright © 2011 Elsevier B.V. All rights reserved.

Natural maximal νμ-ντ mixing

International Nuclear Information System (INIS)

Wetterich, C.

1999-01-01

The naturalness of maximal mixing between myon- and tau-neutrinos is investigated. A spontaneously broken nonabelian generation symmetry can explain a small parameter which governs the deviation from maximal mixing. In many cases all three neutrino masses are almost degenerate. Maximal ν μ -ν τ -mixing suggests that the leading contribution to the light neutrino masses arises from the expectation value of a heavy weak triplet rather than from the seesaw mechanism. In this scenario the deviation from maximal mixing is predicted to be less than about 1%. (Copyright (c) 1999 Elsevier Science B.V., Amsterdam. All rights reserved.)

Efficient Bit-to-Symbol Likelihood Mappings

Science.gov (United States)

Moision, Bruce E.; Nakashima, Michael A.

2010-01-01

This innovation is an efficient algorithm designed to perform bit-to-symbol and symbol-to-bit likelihood mappings that represent a significant portion of the complexity of an error-correction code decoder for high-order constellations. Recent implementation of the algorithm in hardware has yielded an 8- percent reduction in overall area relative to the prior design.

LDR: A Package for Likelihood-Based Sufficient Dimension Reduction

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R. Dennis Cook

2011-03-01

Full Text Available We introduce a new mlab software package that implements several recently proposed likelihood-based methods for sufficient dimension reduction. Current capabilities include estimation of reduced subspaces with a fixed dimension d, as well as estimation of d by use of likelihood-ratio testing, permutation testing and information criteria. The methods are suitable for preprocessing data for both regression and classification. Implementations of related estimators are also available. Although the software is more oriented to command-line operation, a graphical user interface is also provided for prototype computations.

Gaussian maximally multipartite-entangled states

Science.gov (United States)

Facchi, Paolo; Florio, Giuseppe; Lupo, Cosmo; Mancini, Stefano; Pascazio, Saverio

2009-12-01

We study maximally multipartite-entangled states in the context of Gaussian continuous variable quantum systems. By considering multimode Gaussian states with constrained energy, we show that perfect maximally multipartite-entangled states, which exhibit the maximum amount of bipartite entanglement for all bipartitions, only exist for systems containing n=2 or 3 modes. We further numerically investigate the structure of these states and their frustration for n≤7 .

Gaussian maximally multipartite-entangled states

International Nuclear Information System (INIS)

Facchi, Paolo; Florio, Giuseppe; Pascazio, Saverio; Lupo, Cosmo; Mancini, Stefano

2009-01-01

We study maximally multipartite-entangled states in the context of Gaussian continuous variable quantum systems. By considering multimode Gaussian states with constrained energy, we show that perfect maximally multipartite-entangled states, which exhibit the maximum amount of bipartite entanglement for all bipartitions, only exist for systems containing n=2 or 3 modes. We further numerically investigate the structure of these states and their frustration for n≤7.

Bias correction in the hierarchical likelihood approach to the analysis of multivariate survival data.

Science.gov (United States)

Jeon, Jihyoun; Hsu, Li; Gorfine, Malka

2012-07-01

Frailty models are useful for measuring unobserved heterogeneity in risk of failures across clusters, providing cluster-specific risk prediction. In a frailty model, the latent frailties shared by members within a cluster are assumed to act multiplicatively on the hazard function. In order to obtain parameter and frailty variate estimates, we consider the hierarchical likelihood (H-likelihood) approach (Ha, Lee and Song, 2001. Hierarchical-likelihood approach for frailty models. Biometrika 88, 233-243) in which the latent frailties are treated as "parameters" and estimated jointly with other parameters of interest. We find that the H-likelihood estimators perform well when the censoring rate is low, however, they are substantially biased when the censoring rate is moderate to high. In this paper, we propose a simple and easy-to-implement bias correction method for the H-likelihood estimators under a shared frailty model. We also extend the method to a multivariate frailty model, which incorporates complex dependence structure within clusters. We conduct an extensive simulation study and show that the proposed approach performs very well for censoring rates as high as 80%. We also illustrate the method with a breast cancer data set. Since the H-likelihood is the same as the penalized likelihood function, the proposed bias correction method is also applicable to the penalized likelihood estimators.

Utility maximization and mode of payment

NARCIS (Netherlands)

Koning, R.H.; Ridder, G.; Heijmans, R.D.H.; Pollock, D.S.G.; Satorra, A.

2000-01-01

The implications of stochastic utility maximization in a model of choice of payment are examined. Three types of compatibility with utility maximization are distinguished: global compatibility, local compatibility on an interval, and local compatibility on a finite set of points. Keywords:

Communicating likelihoods and probabilities in forecasts of volcanic eruptions

Science.gov (United States)

Doyle, Emma E. H.; McClure, John; Johnston, David M.; Paton, Douglas

2014-02-01

The issuing of forecasts and warnings of natural hazard events, such as volcanic eruptions, earthquake aftershock sequences and extreme weather often involves the use of probabilistic terms, particularly when communicated by scientific advisory groups to key decision-makers, who can differ greatly in relative expertise and function in the decision making process. Recipients may also differ in their perception of relative importance of political and economic influences on interpretation. Consequently, the interpretation of these probabilistic terms can vary greatly due to the framing of the statements, and whether verbal or numerical terms are used. We present a review from the psychology literature on how the framing of information influences communication of these probability terms. It is also unclear as to how people rate their perception of an event's likelihood throughout a time frame when a forecast time window is stated. Previous research has identified that, when presented with a 10-year time window forecast, participants viewed the likelihood of an event occurring ‘today’ as being of less than that in year 10. Here we show that this skew in perception also occurs for short-term time windows (under one week) that are of most relevance for emergency warnings. In addition, unlike the long-time window statements, the use of the phrasing “within the next…” instead of “in the next…” does not mitigate this skew, nor do we observe significant differences between the perceived likelihoods of scientists and non-scientists. This finding suggests that effects occurring due to the shorter time window may be ‘masking’ any differences in perception due to wording or career background observed for long-time window forecasts. These results have implications for scientific advice, warning forecasts, emergency management decision-making, and public information as any skew in perceived event likelihood towards the end of a forecast time window may result in

Modeling gene expression measurement error: a quasi-likelihood approach

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Strimmer Korbinian

2003-03-01

Full Text Available Abstract Background Using suitable error models for gene expression measurements is essential in the statistical analysis of microarray data. However, the true probabilistic model underlying gene expression intensity readings is generally not known. Instead, in currently used approaches some simple parametric model is assumed (usually a transformed normal distribution or the empirical distribution is estimated. However, both these strategies may not be optimal for gene expression data, as the non-parametric approach ignores known structural information whereas the fully parametric models run the risk of misspecification. A further related problem is the choice of a suitable scale for the model (e.g. observed vs. log-scale. Results Here a simple semi-parametric model for gene expression measurement error is presented. In this approach inference is based an approximate likelihood function (the extended quasi-likelihood. Only partial knowledge about the unknown true distribution is required to construct this function. In case of gene expression this information is available in the form of the postulated (e.g. quadratic variance structure of the data. As the quasi-likelihood behaves (almost like a proper likelihood, it allows for the estimation of calibration and variance parameters, and it is also straightforward to obtain corresponding approximate confidence intervals. Unlike most other frameworks, it also allows analysis on any preferred scale, i.e. both on the original linear scale as well as on a transformed scale. It can also be employed in regression approaches to model systematic (e.g. array or dye effects. Conclusions The quasi-likelihood framework provides a simple and versatile approach to analyze gene expression data that does not make any strong distributional assumptions about the underlying error model. For several simulated as well as real data sets it provides a better fit to the data than competing models. In an example it also

Planning Routes Across Economic Terrains: Maximizing Utility, Following Heuristics

Science.gov (United States)

Zhang, Hang; Maddula, Soumya V.; Maloney, Laurence T.

2010-01-01

We designed an economic task to investigate human planning of routes in landscapes where travel in different kinds of terrain incurs different costs. Participants moved their finger across a touch screen from a starting point to a destination. The screen was divided into distinct kinds of terrain and travel within each kind of terrain imposed a cost proportional to distance traveled. We varied costs and spatial configurations of terrains and participants received fixed bonuses minus the total cost of the routes they chose. We first compared performance to a model maximizing gain. All but one of 12 participants failed to adopt least-cost routes and their failure to do so reduced their winnings by about 30% (median value). We tested in detail whether participants’ choices of routes satisfied three necessary conditions (heuristics) for a route to maximize gain. We report failures of one heuristic for 7 out of 12 participants. Last of all, we modeled human performance with the assumption that participants assign subjective utilities to costs and maximize utility. For 7 out 12 participants, the fitted utility function was an accelerating power function of actual cost and for the remaining 5, a decelerating power function. We discuss connections between utility aggregation in route planning and decision under risk. Our task could be adapted to investigate human strategy and optimality of route planning in full-scale landscapes. PMID:21833269

PLANNING ROUTES ACROSS ECONOMIC TERRAINS: MAXIMIZING UTILITY, FOLLOWING HEURISTICS

Directory of Open Access Journals (Sweden)

Hang eZhang

2010-12-01

Full Text Available We designed an economic task to investigate human planning of routes in landscapes where travel in different kinds of terrain incurs different costs. Participants moved their finger across a touch screen from a starting point to a destination. The screen was divided into distinct kinds of terrain and travel within each kind of terrain imposed a cost proportional to distance traveled. We varied costs and spatial configurations of terrains and participants received fixed bonuses minus the total cost of the routes they chose. We first compared performance to a model maximizing gain. All but one of 12 participants failed to adopt least-cost routes and their failure to do so reduced their winnings by about 30% (median value. We tested in detail whether participants’ choices of routes satisfied three necessary conditions (heuristics for a route to maximize gain. We report failures of one heuristic for 7 out of 12 participants. Last of all, we modeled human performance with the assumption that participants assign subjective utilities to costs and maximize utility. For 7 out 12 participants, the fitted utility function was an accelerating power function of actual cost and for the remaining 5, a decelerating power function. We discuss connections between utility aggregation in route planning and decision under risk. Our task could be adapted to investigate human strategy and optimality of route planning in full-scale landscapes.

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.

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.

How to Maximize the Likelihood Function for a DSGE Model

DEFF Research Database (Denmark)

Andreasen, Martin Møller

This paper extends two optimization routines to deal with objective functions for DSGE models. The optimization routines are i) a version of Simulated Annealing developed by Corana, Marchesi & Ridella (1987), and ii) the evolutionary algorithm CMA-ES developed by Hansen, Müller & Koumoutsakos (2003...

Susceptibility, likelihood to be diagnosed, worry and fear for contracting Lyme disease.

Science.gov (United States)

Fogel, Joshua; Chawla, Gurasees S

Risk perception and psychological concerns are relevant for understanding how people view Lyme disease. This study investigates the four separate outcomes of susceptibility, likelihood to be diagnosed, worry, and fear for contracting Lyme disease. University students (n=713) were surveyed about demographics, perceived health, Lyme disease knowledge, Lyme disease preventive behaviors, Lyme disease history, and Lyme disease miscellaneous variables. We found that women were associated with increased susceptibility and fear. Asian/Asian-American race/ethnicity was associated with increased worry and fear. Perceived good health was associated with increased likelihood to be diagnosed, worry, and fear. Correct knowledge was associated with increased susceptibility and likelihood to be diagnosed. Those who typically spend a lot of time outdoors were associated with increased susceptibility, likelihood to be diagnosed, worry, and fear. In conclusion, healthcare providers and public health campaigns should address susceptibility, likelihood to be diagnosed, worry, and fear about Lyme disease, and should particularly target women and Asians/Asian-Americans to address any possible misconceptions and/or offer effective coping strategies. Copyright © 2016 King Saud Bin Abdulaziz University for Health Sciences. Published by Elsevier Ltd. All rights reserved.

Activity versus outcome maximization in time management.

Science.gov (United States)

Malkoc, Selin A; Tonietto, Gabriela N

2018-04-30

Feeling time-pressed has become ubiquitous. Time management strategies have emerged to help individuals fit in more of their desired and necessary activities. We provide a review of these strategies. In doing so, we distinguish between two, often competing, motives people have in managing their time: activity maximization and outcome maximization. The emerging literature points to an important dilemma: a given strategy that maximizes the number of activities might be detrimental to outcome maximization. We discuss such factors that might hinder performance in work tasks and enjoyment in leisure tasks. Finally, we provide theoretically grounded recommendations that can help balance these two important goals in time management. Published by Elsevier Ltd.

Massive optimal data compression and density estimation for scalable, likelihood-free inference in cosmology

Science.gov (United States)

Alsing, Justin; Wandelt, Benjamin; Feeney, Stephen

2018-03-01

Many statistical models in cosmology can be simulated forwards but have intractable likelihood functions. Likelihood-free inference methods allow us to perform Bayesian inference from these models using only forward simulations, free from any likelihood assumptions or approximations. Likelihood-free inference generically involves simulating mock data and comparing to the observed data; this comparison in data-space suffers from the curse of dimensionality and requires compression of the data to a small number of summary statistics to be tractable. In this paper we use massive asymptotically-optimal data compression to reduce the dimensionality of the data-space to just one number per parameter, providing a natural and optimal framework for summary statistic choice for likelihood-free inference. Secondly, we present the first cosmological application of Density Estimation Likelihood-Free Inference (DELFI), which learns a parameterized model for joint distribution of data and parameters, yielding both the parameter posterior and the model evidence. This approach is conceptually simple, requires less tuning than traditional Approximate Bayesian Computation approaches to likelihood-free inference and can give high-fidelity posteriors from orders of magnitude fewer forward simulations. As an additional bonus, it enables parameter inference and Bayesian model comparison simultaneously. We demonstrate Density Estimation Likelihood-Free Inference with massive data compression on an analysis of the joint light-curve analysis supernova data, as a simple validation case study. We show that high-fidelity posterior inference is possible for full-scale cosmological data analyses with as few as ˜104 simulations, with substantial scope for further improvement, demonstrating the scalability of likelihood-free inference to large and complex cosmological datasets.

Learning to maximize reward rate: a model based on semi-Markov decision processes.

Science.gov (United States)

Khodadadi, Arash; Fakhari, Pegah; Busemeyer, Jerome R

2014-01-01

WHEN ANIMALS HAVE TO MAKE A NUMBER OF DECISIONS DURING A LIMITED TIME INTERVAL, THEY FACE A FUNDAMENTAL PROBLEM: how much time they should spend on each decision in order to achieve the maximum possible total outcome. Deliberating more on one decision usually leads to more outcome but less time will remain for other decisions. In the framework of sequential sampling models, the question is how animals learn to set their decision threshold such that the total expected outcome achieved during a limited time is maximized. The aim of this paper is to provide a theoretical framework for answering this question. To this end, we consider an experimental design in which each trial can come from one of the several possible "conditions." A condition specifies the difficulty of the trial, the reward, the penalty and so on. We show that to maximize the expected reward during a limited time, the subject should set a separate value of decision threshold for each condition. We propose a model of learning the optimal value of decision thresholds based on the theory of semi-Markov decision processes (SMDP). In our model, the experimental environment is modeled as an SMDP with each "condition" being a "state" and the value of decision thresholds being the "actions" taken in those states. The problem of finding the optimal decision thresholds then is cast as the stochastic optimal control problem of taking actions in each state in the corresponding SMDP such that the average reward rate is maximized. Our model utilizes a biologically plausible learning algorithm to solve this problem. The simulation results show that at the beginning of learning the model choses high values of decision threshold which lead to sub-optimal performance. With experience, however, the model learns to lower the value of decision thresholds till finally it finds the optimal values.

Should I Text or Call Here? A Situation-Based Analysis of Drivers' Perceived Likelihood of Engaging in Mobile Phone Multitasking.

Science.gov (United States)

Oviedo-Trespalacios, Oscar; Haque, Md Mazharul; King, Mark; Washington, Simon

2018-05-29

This study investigated how situational characteristics typically encountered in the transport system influence drivers' perceived likelihood of engaging in mobile phone multitasking. The impacts of mobile phone tasks, perceived environmental complexity/risk, and drivers' individual differences were evaluated as relevant individual predictors within the behavioral adaptation framework. An innovative questionnaire, which includes randomized textual and visual scenarios, was administered to collect data from a sample of 447 drivers in South East Queensland-Australia (66% females; n = 296). The likelihood of engaging in a mobile phone task across various scenarios was modeled by a random parameters ordered probit model. Results indicated that drivers who are female, are frequent users of phones for texting/answering calls, have less favorable attitudes towards safety, and are highly disinhibited were more likely to report stronger intentions of engaging in mobile phone multitasking. However, more years with a valid driving license, self-efficacy toward self-regulation in demanding traffic conditions and police enforcement, texting tasks, and demanding traffic conditions were negatively related to self-reported likelihood of mobile phone multitasking. The unobserved heterogeneity warned of riskier groups among female drivers and participants who need a lot of convincing to believe that multitasking while driving is dangerous. This research concludes that behavioral adaptation theory is a robust framework explaining self-regulation of distracted drivers. © 2018 Society for Risk Analysis.

Comparative polygenic analysis of maximal ethanol accumulation capacity and tolerance to high ethanol levels of cell proliferation in yeast.

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Thiago M Pais

2013-06-01

Full Text Available The yeast Saccharomyces cerevisiae is able to accumulate ≥17% ethanol (v/v by fermentation in the absence of cell proliferation. The genetic basis of this unique capacity is unknown. Up to now, all research has focused on tolerance of yeast cell proliferation to high ethanol levels. Comparison of maximal ethanol accumulation capacity and ethanol tolerance of cell proliferation in 68 yeast strains showed a poor correlation, but higher ethanol tolerance of cell proliferation clearly increased the likelihood of superior maximal ethanol accumulation capacity. We have applied pooled-segregant whole-genome sequence analysis to identify the polygenic basis of these two complex traits using segregants from a cross of a haploid derivative of the sake strain CBS1585 and the lab strain BY. From a total of 301 segregants, 22 superior segregants accumulating ≥17% ethanol in small-scale fermentations and 32 superior segregants growing in the presence of 18% ethanol, were separately pooled and sequenced. Plotting SNP variant frequency against chromosomal position revealed eleven and eight Quantitative Trait Loci (QTLs for the two traits, respectively, and showed that the genetic basis of the two traits is partially different. Fine-mapping and Reciprocal Hemizygosity Analysis identified ADE1, URA3, and KIN3, encoding a protein kinase involved in DNA damage repair, as specific causative genes for maximal ethanol accumulation capacity. These genes, as well as the previously identified MKT1 gene, were not linked in this genetic background to tolerance of cell proliferation to high ethanol levels. The superior KIN3 allele contained two SNPs, which are absent in all yeast strains sequenced up to now. This work provides the first insight in the genetic basis of maximal ethanol accumulation capacity in yeast and reveals for the first time the importance of DNA damage repair in yeast ethanol tolerance.

Quadratic maximization on the unit simplex: structure, stability, genericity and application in biology

NARCIS (Netherlands)

Still, Georg J.; Ahmed, F.

The paper deals with the simple but important problem of maximizing a (nonconvex) quadratic function on the unit simplex. This program is directly related to the concept of evolutionarily stable strategies (ESS) in biology. We discuss this relation and study optimality conditions, stability and

Maximizing Entropy over Markov Processes

DEFF Research Database (Denmark)

Biondi, Fabrizio; Legay, Axel; Nielsen, Bo Friis

2013-01-01

The channel capacity of a deterministic system with confidential data is an upper bound on the amount of bits of data an attacker can learn from the system. We encode all possible attacks to a system using a probabilistic specification, an Interval Markov Chain. Then the channel capacity...... as a reward function, a polynomial algorithm to verify the existence of an system maximizing entropy among those respecting a specification, a procedure for the maximization of reward functions over Interval Markov Chains and its application to synthesize an implementation maximizing entropy. We show how...... to use Interval Markov Chains to model abstractions of deterministic systems with confidential data, and use the above results to compute their channel capacity. These results are a foundation for ongoing work on computing channel capacity for abstractions of programs derived from code....

Maximizing entropy over Markov processes

DEFF Research Database (Denmark)

Biondi, Fabrizio; Legay, Axel; Nielsen, Bo Friis

2014-01-01

The channel capacity of a deterministic system with confidential data is an upper bound on the amount of bits of data an attacker can learn from the system. We encode all possible attacks to a system using a probabilistic specification, an Interval Markov Chain. Then the channel capacity...... as a reward function, a polynomial algorithm to verify the existence of a system maximizing entropy among those respecting a specification, a procedure for the maximization of reward functions over Interval Markov Chains and its application to synthesize an implementation maximizing entropy. We show how...... to use Interval Markov Chains to model abstractions of deterministic systems with confidential data, and use the above results to compute their channel capacity. These results are a foundation for ongoing work on computing channel capacity for abstractions of programs derived from code. © 2014 Elsevier...

HEALTH INSURANCE: CONTRIBUTIONS AND REIMBURSEMENT MAXIMAL

CERN Document Server

HR Division

2000-01-01

Affected by both the salary adjustment index on 1.1.2000 and the evolution of the staff members and fellows population, the average reference salary, which is used as an index for fixed contributions and reimbursement maximal, has changed significantly. An adjustment of the amounts of the reimbursement maximal and the fixed contributions is therefore necessary, as from 1 January 2000.Reimbursement maximalThe revised reimbursement maximal will appear on the leaflet summarising the benefits for the year 2000, which will soon be available from the divisional secretariats and from the AUSTRIA office at CERN.Fixed contributionsThe fixed contributions, applicable to some categories of voluntarily insured persons, are set as follows (amounts in CHF for monthly contributions):voluntarily insured member of the personnel, with complete coverage:815,- (was 803,- in 1999)voluntarily insured member of the personnel, with reduced coverage:407,- (was 402,- in 1999)voluntarily insured no longer dependent child:326,- (was 321...

Cardiac function and oxygen saturation during maximal breath-holding in air and during whole-body surface immersion.

Science.gov (United States)

Marabotti, Claudio; Piaggi, Paolo; Menicucci, Danilo; Passera, Mirko; Benassi, Antonio; Bedini, Remo; L'Abbate, Antonio

2013-09-01

The magnitude of the oxygen-sparing effect induced by the diving response in humans is still under debate. We wished to compare cardiovascular changes during maximal breath-holding (BH) in air and during whole-body immersion at the surface in a group of BH divers. Twenty-one divers performed a maximal static apnea in air or during whole-body immersion. Dopplerechocardiography, arterial blood pressure and haemoglobin saturation (SaO₂) were obtained at the beginning of, and at 1/3, 2/3 and maximal BH time. BH time was on the average 3.6 ± 0.4 min, with no differences between the two conditions. SaO₂ significantly decreased during BH in both conditions, but was significantly higher during immersion as compared to the dry (P = 0.04). In both conditions, BH induced a significant linear increase in right ventricular diameter (P whole-body immersion, associated with reduced LV ejection fraction and progressive hindrance to diastolic filling. For a similar apnea duration, SaO₂ decreased less during immersed BH, indicating an O₂-sparing effect of diving, suggesting that interruption of apnea was not triggered by a threshold critical value of blood O₂ desaturation.

Nearly Efficient Likelihood Ratio Tests for Seasonal Unit Roots

DEFF Research Database (Denmark)

Jansson, Michael; Nielsen, Morten Ørregaard

In an important generalization of zero frequency autore- gressive unit root tests, Hylleberg, Engle, Granger, and Yoo (1990) developed regression-based tests for unit roots at the seasonal frequencies in quarterly time series. We develop likelihood ratio tests for seasonal unit roots and show...... that these tests are "nearly efficient" in the sense of Elliott, Rothenberg, and Stock (1996), i.e. that their local asymptotic power functions are indistinguishable from the Gaussian power envelope. Currently available nearly efficient testing procedures for seasonal unit roots are regression-based and require...... the choice of a GLS detrending parameter, which our likelihood ratio tests do not....

On the maximal diphoton width

CERN Document Server

Salvio, Alberto; Strumia, Alessandro; Urbano, Alfredo

2016-01-01

Motivated by the 750 GeV diphoton excess found at LHC, we compute the maximal width into $\\gamma\\gamma$ that a neutral scalar can acquire through a loop of charged fermions or scalars as function of the maximal scale at which the theory holds, taking into account vacuum (meta)stability bounds. We show how an extra gauge symmetry can qualitatively weaken such bounds, and explore collider probes and connections with Dark Matter.

Approaching maximal performance of longitudinal beam compression in induction accelerator drivers

International Nuclear Information System (INIS)

Mark, J.W.K.; Ho, D.D.M.; Brandon, S.T.; Chang, C.L.; Drobot, A.T.; Faltens, A.; Lee, E.P.; Krafft, G.A.

1986-01-01

Longitudinal beam compression occurs before final focus and fusion chamber beam transport and is a key process determining initial conditions for final focus hardware. Determining the limits for maximal performance of key accelerator components is an essential element of the effort to reduce driver costs. Studies directed towards defining the limits of final beam compression including considerations such as maximal available compression, effects of longitudinal dispersion and beam emittance, combining pulse-shaping with beam compression to reduce the total number of beam manipulators, etc., are given. Several possible techniques are illustrated for utilizing the beam compression process to provide the pulse shapes required by a number of targets. Without such capabilities to shape the pulse, an additional factor of two or so of beam energy would be required by the targets

The vortex-finding property of maximal center (and other) gauges

International Nuclear Information System (INIS)

Faber, M.; Greensite, J.; Olejnik, S.; Yamada, D.

1999-01-01

The authors argue that the vortex-finding property of maximal center gauge, i.e. the ability of this gauge to locate center vortices inserted by hand on any given lattice, is the key to its success in extracting the vortex content of thermalized lattice configurations. The authors explain how this property comes about, and why it is expected not only in maximal center gauge, but also in an infinite class of gauge conditions based on adjoint-representation link variables. In principle, the vortex-finding property can be foiled by Gribov copies. This fact is relevant to a gauge-fixing procedure devised by Kovacs and Tomboulis, where they show that the loss of center dominance, found in their procedure, is explained by a corresponding loss of the vortex-finding property. The dependence of center dominance on the vortex-finding property is demonstrated numerically in a number of other gauges

Behavior of the maximal solution of the Cauchy problem for some nonlinear pseudoparabolic equation as $|x|oinfty$

Directory of Open Access Journals (Sweden)

Tatiana Kavitova

2012-08-01

Full Text Available We prove a comparison principle for solutions of the Cauchy problem of the nonlinear pseudoparabolic equation $u_t=Delta u_t+ Deltavarphi(u +h(t,u$ with nonnegative bounded initial data. We show stabilization of a maximal solution to a maximal solution of the Cauchy problem for the corresponding ordinary differential equation $vartheta'(t=h(t,vartheta$ as $|x|oinfty$ under certain conditions on an initial datum.

Upper Limb Static-Stretching Protocol Decreases Maximal Concentric Jump Performance

Directory of Open Access Journals (Sweden)

Paulo H. Marchetti

2014-12-01

Full Text Available The purpose of the present study was to evaluate the acute effects of an upper limb static-stretching (SS protocol on the maximal concentric jump performance. We recruited 25 young healthy, male, resistance trained individuals (stretched group, n = 15 and control group, n = 10 in this study. The randomized between group experimental protocol consisted of a three trials of maximal concentric jump task, before and after a SS of the upper limb. Vertical ground reaction forces (vGRF and surface electromyography (sEMG of both gastrocnemius lateralis (GL and vastus lateralis (VL were acquired. An extensive SS was employed consisting of ten stretches of 30 seconds, with 15 seconds of rest, and 70-90% of the point of discomfort (POD. ANOVA (2x2 (group x condition was used for shoulder joint range of motion (ROM, vGRF and sEMG. A significant interaction for passive ROM of the shoulder joint revealed significant increases between pre- and post-SS protocol (p < 0.001. A significant interaction demonstrated decreased peak force and an increased peak propulsion duration between pre- and post-stretching only for stretch group (p = 0.021, and p = 0.024, respectively. There was a significant main effect between groups (stretch and control for peak force for control group (p = 0.045. Regarding sEMG variables, there were no significant differences between groups (control versus stretched or condition (pre-stretching versus post-stretching for the peak amplitude of RMS and IEMG for both muscles (VL and GL. In conclusion, an acute extensive SS can increase the shoulder ROM, and negatively affect both the propulsion duration and peak force of the maximal concentric jump, without providing significant changes in muscle activation.

The slack test does not assess maximal shortening velocity of muscle fascicle in human.

Science.gov (United States)

Hager, Robin; Dorel, Sylvain; Nordez, Antoine; Rabita, Giuseppe; Couturier, Antoine; Hauraix, Hugo; Duchateau, Jacques; Guilhem, Gaël

2018-06-14

The application of a series of extremely high accelerative motor-driven quick releases while muscles contract isometrically (i.e. slack test) has been proposed to assess unloaded velocity in human muscle. This study aimed to measure gastrocnemius medialis fascicle (V F ) and tendinous tissues shortening velocity during motor-driven quick releases performed at various activation levels to assess the applicability of the slack test method in human. Maximal fascicle shortening velocity and joint velocity recorded during quick releases and during fast contraction without external load (ballistic condition) were compared. Gastrocnemius medialis fascicle behaviour was investigated from 25 participants using high-frame rate ultrasound during quick releases performed at various activation levels (from 0% to 60% of maximal voluntary isometric torque) and ballistic contractions. Unloaded joint velocity calculated using the slack test method increased whereas V F decreased with muscle activation level (P≤0.03). Passive and low-level quick releases elicited higher V F values (≥ 41.4±9.7 cm.s -1 ) compared to ballistic condition (36.3±8.7 cm.s -1 ), while quick releases applied at 60% of maximal voluntary isometric torque produced the lowest V F These findings suggest that initial fascicle length, complex fascicle-tendon interactions, unloading reflex and motor-driven movement pattern strongly influence and limit the shortening velocity achieved during the slack test. Furthermore, V F elicited by quick releases is likely to reflect substantial contributions of passive processes. Therefore, the slack test is not appropriate to assess maximal muscle shortening velocity in vivo. © 2018. Published by The Company of Biologists Ltd.

Generalized empirical likelihood methods for analyzing longitudinal data

KAUST Repository

Wang, S.; Qian, L.; Carroll, R. J.

2010-01-01

Efficient estimation of parameters is a major objective in analyzing longitudinal data. We propose two generalized empirical likelihood based methods that take into consideration within-subject correlations. A nonparametric version of the Wilks

Lovelock black holes with maximally symmetric horizons

Energy Technology Data Exchange (ETDEWEB)

Maeda, Hideki; Willison, Steven; Ray, Sourya, E-mail: hideki@cecs.cl, E-mail: willison@cecs.cl, E-mail: ray@cecs.cl [Centro de Estudios CientIficos (CECs), Casilla 1469, Valdivia (Chile)

2011-08-21

We investigate some properties of n( {>=} 4)-dimensional spacetimes having symmetries corresponding to the isometries of an (n - 2)-dimensional maximally symmetric space in Lovelock gravity under the null or dominant energy condition. The well-posedness of the generalized Misner-Sharp quasi-local mass proposed in the past study is shown. Using this quasi-local mass, we clarify the basic properties of the dynamical black holes defined by a future outer trapping horizon under certain assumptions on the Lovelock coupling constants. The C{sup 2} vacuum solutions are classified into four types: (i) Schwarzschild-Tangherlini-type solution; (ii) Nariai-type solution; (iii) special degenerate vacuum solution; and (iv) exceptional vacuum solution. The conditions for the realization of the last two solutions are clarified. The Schwarzschild-Tangherlini-type solution is studied in detail. We prove the first law of black-hole thermodynamics and present the expressions for the heat capacity and the free energy.

Estimation Methods for Non-Homogeneous Regression - Minimum CRPS vs Maximum Likelihood

Science.gov (United States)

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

Estimation of Model's Marginal likelihood Using Adaptive Sparse Grid Surrogates in Bayesian Model Averaging

Science.gov (United States)

Zeng, X.

2015-12-01

A large number of model executions are required to obtain alternative conceptual models' predictions and their posterior probabilities in Bayesian model averaging (BMA). The posterior model probability is estimated through models' marginal likelihood and prior probability. The heavy computation burden hinders the implementation of BMA prediction, especially for the elaborated marginal likelihood estimator. For overcoming the computation burden of BMA, an adaptive sparse grid (SG) stochastic collocation method is used to build surrogates for alternative conceptual models through the numerical experiment of a synthetical groundwater model. BMA predictions depend on model posterior weights (or marginal likelihoods), and this study also evaluated four marginal likelihood estimators, including arithmetic mean estimator (AME), harmonic mean estimator (HME), stabilized harmonic mean estimator (SHME), and thermodynamic integration estimator (TIE). The results demonstrate that TIE is accurate in estimating conceptual models' marginal likelihoods. The BMA-TIE has better predictive performance than other BMA predictions. TIE has high stability for estimating conceptual model's marginal likelihood. The repeated estimated conceptual model's marginal likelihoods by TIE have significant less variability than that estimated by other estimators. In addition, the SG surrogates are efficient to facilitate BMA predictions, especially for BMA-TIE. The number of model executions needed for building surrogates is 4.13%, 6.89%, 3.44%, and 0.43% of the required model executions of BMA-AME, BMA-HME, BMA-SHME, and BMA-TIE, respectively.

Parallelization of maximum likelihood fits with OpenMP and CUDA

CERN Document Server

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...

ATP and phosphocreatine utilization in single human muscle fibres during the development of maximal power output at elevated muscle temperatures.

Science.gov (United States)

Gray, Stuart R; Söderlund, Karin; Ferguson, Richard A

2008-05-01

In this study, we examined the effect of muscle temperature (Tm) on adenosine triphosphate (ATP) and phosphocreatine utilization in single muscle fibres during the development of maximal power output in humans. Six male participants performed a 6-s maximal sprint on a friction-braked cycle ergometer under both normal (Tm = 34.3 degrees C, s = 0.6) and elevated (T(m) = 37.3 degrees C, s = 0.2) muscle temperature conditions. During the elevated condition, muscle temperature of the legs was raised, passively, by hot water immersion followed by wrapping in electrically heated blankets. Muscle biopsies were taken from the vastus lateralis before and immediately after exercise. Freeze-dried single fibres were dissected, characterized according to myosin heavy chain composition, and analysed for ATP and phosphocreatine content. Single fibres were classified as: type I, IIA, IIAX25 (1 - 25% IIX isoform), IIAX50 (26 - 50% IIX), IIAX75 (51 - 75% IIX), or IIAX100 (76 - 100% IIX). Maximal power output and pedal rate were both greater (P < 0.05) during the elevated condition by 258 W (s = 110) and 22 rev . min(-1) (s = 6), respectively. In both conditions, phosphocreatine content decreased significantly in all fibre types, with a greater decrease during the elevated condition in type IIA fibres (P < 0.01). Adenosine triphosphate content was also reduced to a greater (P < 0.01) extent in type IIA fibres during the elevated condition. The results of the present study indicate that after passive elevation of muscle temperature, there was a greater decrease in ATP and phosphocreatine content in type IIA fibres than in the normal trial, which contributed to the higher maximal power output.

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 𝒢0 law. This paper deals with amplitude data, so the 𝒢A0 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 𝒢A0 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.

Unbinned likelihood maximisation framework for neutrino clustering in Python

Energy Technology Data Exchange (ETDEWEB)

Coenders, Stefan [Technische Universitaet Muenchen, Boltzmannstr. 2, 85748 Garching (Germany)

2016-07-01

Albeit having detected an astrophysical neutrino flux with IceCube, sources of astrophysical neutrinos remain hidden up to now. A detection of a neutrino point source is a smoking gun for hadronic processes and acceleration of cosmic rays. The search for neutrino sources has many degrees of freedom, for example steady versus transient, point-like versus extended sources, et cetera. Here, we introduce a Python framework designed for unbinned likelihood maximisations as used in searches for neutrino point sources by IceCube. Implementing source scenarios in a modular way, likelihood searches on various kinds can be implemented in a user-friendly way, without sacrificing speed and memory management.

Dimension-Independent Likelihood-Informed MCMC

KAUST Repository

Cui, Tiangang; Law, Kody; Marzouk, Youssef

2015-01-01

Many Bayesian inference problems require exploring the posterior distribution of high-dimensional parameters, which in principle can be described as functions. By exploiting low-dimensional structure in the change from prior to posterior [distributions], we introduce a suite of MCMC samplers that can adapt to the complex structure of the posterior distribution, yet are well-defined on function space. Posterior sampling in nonlinear inverse problems arising from various partial di erential equations and also a stochastic differential equation are used to demonstrate the e ciency of these dimension-independent likelihood-informed samplers.

Dimension-Independent Likelihood-Informed MCMC

KAUST Repository

Cui, Tiangang

2015-01-07

Many Bayesian inference problems require exploring the posterior distribution of high-dimensional parameters, which in principle can be described as functions. By exploiting low-dimensional structure in the change from prior to posterior [distributions], we introduce a suite of MCMC samplers that can adapt to the complex structure of the posterior distribution, yet are well-defined on function space. Posterior sampling in nonlinear inverse problems arising from various partial di erential equations and also a stochastic differential equation are used to demonstrate the e ciency of these dimension-independent likelihood-informed samplers.

COSMIC MICROWAVE BACKGROUND LIKELIHOOD APPROXIMATION BY A GAUSSIANIZED BLACKWELL-RAO ESTIMATOR

International Nuclear Information System (INIS)

Rudjord, Oe.; Groeneboom, N. E.; Eriksen, H. K.; Huey, Greg; Gorski, K. M.; Jewell, J. B.

2009-01-01

We introduce a new cosmic microwave background (CMB) temperature likelihood approximation called the Gaussianized Blackwell-Rao estimator. This estimator is derived by transforming the observed marginal power spectrum distributions obtained by the CMB Gibbs sampler into standard univariate Gaussians, and then approximating their joint transformed distribution by a multivariate Gaussian. The method is exact for full-sky coverage and uniform noise and an excellent approximation for sky cuts and scanning patterns relevant for modern satellite experiments such as the Wilkinson Microwave Anisotropy Probe (WMAP) and Planck. The result is a stable, accurate, and computationally very efficient CMB temperature likelihood representation that allows the user to exploit the unique error propagation capabilities of the Gibbs sampler to high ls. A single evaluation of this estimator between l = 2 and 200 takes ∼0.2 CPU milliseconds, while for comparison, a singe pixel space likelihood evaluation between l = 2 and 30 for a map with ∼2500 pixels requires ∼20 s. We apply this tool to the five-year WMAP temperature data, and re-estimate the angular temperature power spectrum, C l , and likelihood, L(C l ), for l ≤ 200, and derive new cosmological parameters for the standard six-parameter ΛCDM model. Our spectrum is in excellent agreement with the official WMAP spectrum, but we find slight differences in the derived cosmological parameters. Most importantly, the spectral index of scalar perturbations is n s = 0.973 ± 0.014, 1.9σ away from unity and 0.6σ higher than the official WMAP result, n s = 0.965 ± 0.014. This suggests that an exact likelihood treatment is required to higher ls than previously believed, reinforcing and extending our conclusions from the three-year WMAP analysis. In that case, we found that the suboptimal likelihood approximation adopted between l = 12 and 30 by the WMAP team biased n s low by 0.4σ, while here we find that the same approximation

Fatigue during maximal sprint cycling: unique role of cumulative contraction cycles.

Science.gov (United States)

Tomas, Aleksandar; Ross, Emma Z; Martin, James C

2010-07-01

Maximal cycling power has been reported to decrease more rapidly when performed with increased pedaling rates. Increasing pedaling rate imposes two constraints on the neuromuscular system: 1) decreased time for muscle excitation and relaxation and 2) increased muscle shortening velocity. Using two crank lengths allows the effects of time and shortening velocity to be evaluated separately. We conducted this investigation to determine whether the time available for excitation and relaxation or the muscle shortening velocity was mainly responsible for the increased rate of fatigue previously observed with increased pedaling rates and to evaluate the influence of other possible fatiguing constraints. Seven trained cyclists performed 30-s maximal isokinetic cycling trials using two crank lengths: 120 and 220 mm. Pedaling rate was optimized for maximum power for each crank length: 135 rpm for the 120-mm cranks (1.7 m x s(-1) pedal speed) and 109 rpm for the 220-mm cranks (2.5 m x s(-1) pedal speed). Power was recorded with an SRM power meter. Crank length did not affect peak power: 999 +/- 276 W for the 120-mm crank versus 1001 +/- 289 W for the 220-mm crank. Fatigue index was greater (58.6% +/- 3.7% vs 52.4% +/- 4.8%, P < 0.01), and total work was less (20.0 +/- 1.8 vs 21.4 +/- 2.0 kJ, P < 0.01) with the higher pedaling rate-shorter crank condition. Regression analyses indicated that the power for the two conditions was most highly related to cumulative work (r2 = 0.94) and to cumulative cycles (r2 = 0.99). These results support previous findings and confirm that pedaling rate, rather than pedal speed, was the main factor influencing fatigue. Our novel result was that power decreased by a similar increment with each crank revolution for the two conditions, indicating that each maximal muscular contraction induced a similar amount of fatigue.

Physical renormalization condition for de Sitter QED

Science.gov (United States)

Hayashinaka, Takahiro; Xue, She-Sheng

2018-05-01

We considered a new renormalization condition for the vacuum expectation values of the scalar and spinor currents induced by a homogeneous and constant electric field background in de Sitter spacetime. Following a semiclassical argument, the condition named maximal subtraction imposes the exponential suppression on the massive charged particle limit of the renormalized currents. The maximal subtraction changes the behaviors of the induced currents previously obtained by the conventional minimal subtraction scheme. The maximal subtraction is favored for a couple of physically decent predictions including the identical asymptotic behavior of the scalar and spinor currents, the removal of the IR hyperconductivity from the scalar current, and the finite current for the massless fermion.

Generalized Empirical Likelihood-Based Focused Information Criterion and Model Averaging

Directory of Open Access Journals (Sweden)

Naoya Sueishi

2013-07-01

Full Text Available This paper develops model selection and averaging methods for moment restriction models. We first propose a focused information criterion based on the generalized empirical likelihood estimator. We address the issue of selecting an optimal model, rather than a correct model, for estimating a specific parameter of interest. Then, this study investigates a generalized empirical likelihood-based model averaging estimator that minimizes the asymptotic mean squared error. A simulation study suggests that our averaging estimator can be a useful alternative to existing post-selection estimators.

Nearly Efficient Likelihood Ratio Tests of the Unit Root Hypothesis

DEFF Research Database (Denmark)

Jansson, Michael; Nielsen, Morten Ørregaard

Seemingly absent from the arsenal of currently available "nearly efficient" testing procedures for the unit root hypothesis, i.e. tests whose local asymptotic power functions are indistinguishable from the Gaussian power envelope, is a test admitting a (quasi-)likelihood ratio interpretation. We...... show that the likelihood ratio unit root test derived in a Gaussian AR(1) model with standard normal innovations is nearly efficient in that model. Moreover, these desirable properties carry over to more complicated models allowing for serially correlated and/or non-Gaussian innovations....

Mixtures of maximally entangled pure states

Energy Technology Data Exchange (ETDEWEB)

Flores, M.M., E-mail: mflores@nip.up.edu.ph; Galapon, E.A., E-mail: eric.galapon@gmail.com

2016-09-15

We study the conditions when mixtures of maximally entangled pure states remain entangled. We found that the resulting mixed state remains entangled when the number of entangled pure states to be mixed is less than or equal to the dimension of the pure states. For the latter case of mixing a number of pure states equal to their dimension, we found that the mixed state is entangled provided that the entangled pure states to be mixed are not equally weighted. We also found that one can restrict the set of pure states that one can mix from in order to ensure that the resulting mixed state is genuinely entangled. Also, we demonstrate how these results could be applied as a way to detect entanglement in mixtures of the entangled pure states with noise.

Depression and Chronic Health Conditions Among Latinos: The Role of Social Networks.

Science.gov (United States)

Soto, Sandra; Arredondo, Elva M; Villodas, Miguel T; Elder, John P; Quintanar, Elena; Madanat, Hala

2016-12-01

The purpose of this study was to examine the "buffering hypothesis" of social network characteristics in the association between chronic conditions and depression among Latinos. Cross-sectional self-report data from the San Diego Prevention Research Center's community survey of Latinos were used (n = 393). Separate multiple logistic regression models tested the role of chronic conditions and social network characteristics in the likelihood of moderate-to-severe depressive symptoms. Having a greater proportion of the network comprised of friends increased the likelihood of depression among those with high cholesterol. Having a greater proportion of women in the social network was directly related to the increased likelihood of depression, regardless of the presence of chronic health conditions. Findings suggest that network characteristics may play a role in the link between chronic conditions and depression among Latinos. Future research should explore strategies targeting the social networks of Latinos to improve health outcomes.

A Criterion to Identify Maximally Entangled Four-Qubit State

International Nuclear Information System (INIS)

Zha Xinwei; Song Haiyang; Feng Feng

2011-01-01

Paolo Facchi, et al. [Phys. Rev. A 77 (2008) 060304(R)] presented a maximally multipartite entangled state (MMES). Here, we give a criterion for the identification of maximally entangled four-qubit states. Using this criterion, we not only identify some existing maximally entangled four-qubit states in the literature, but also find several new maximally entangled four-qubit states as well. (general)

Development of likelihood estimation method for criticality accidents of mixed oxide fuel fabrication facilities

International Nuclear Information System (INIS)

Tamaki, Hitoshi; Yoshida, Kazuo; Kimoto, Tatsuya; Hamaguchi, Yoshikane

2010-01-01

A criticality accident in a MOX fuel fabrication facility may occur depending on several parameters, such as mass inventory and plutonium enrichment. MOX handling units in the facility are designed and operated based on the double contingency principle to prevent criticality accidents. Control failures of at least two parameters are needed for the occurrence of criticality accident. To evaluate the probability of such control failures, the criticality conditions of each parameter for a specific handling unit are necessary for accident scenario analysis to be clarified quantitatively with a criticality analysis computer code. In addition to this issue, a computer-based control system for mass inventory is planned to be installed into MOX handling equipment in a commercial MOX fuel fabrication plant. The reliability analysis is another important issue in evaluating the likelihood of control failure caused by software malfunction. A likelihood estimation method for criticality accident has been developed with these issues been taken into consideration. In this paper, an example of analysis with the proposed method and the applicability of the method are also shown through a trial application to a model MOX fabrication facility. (author)

The likelihood ratio as a random variable for linked markers in kinship analysis.

Science.gov (United States)

Egeland, Thore; Slooten, Klaas

2016-11-01

The likelihood ratio is the fundamental quantity that summarizes the evidence in forensic cases. Therefore, it is important to understand the theoretical properties of this statistic. This paper is the last in a series of three, and the first to study linked markers. We show that for all non-inbred pairwise kinship comparisons, the expected likelihood ratio in favor of a type of relatedness depends on the allele frequencies only via the number of alleles, also for linked markers, and also if the true relationship is another one than is tested for by the likelihood ratio. Exact expressions for the expectation and variance are derived for all these cases. Furthermore, we show that the expected likelihood ratio is a non-increasing function if the recombination rate increases between 0 and 0.5 when the actual relationship is the one investigated by the LR. Besides being of theoretical interest, exact expressions such as obtained here can be used for software validation as they allow to verify the correctness up to arbitrary precision. The paper also presents results and advice of practical importance. For example, we argue that the logarithm of the likelihood ratio behaves in a fundamentally different way than the likelihood ratio itself in terms of expectation and variance, in agreement with its interpretation as weight of evidence. Equipped with the results presented and freely available software, one may check calculations and software and also do power calculations.

A Walk on the Wild Side: The Impact of Music on Risk-Taking Likelihood.

Science.gov (United States)

Enström, Rickard; Schmaltz, Rodney

2017-01-01

From a marketing perspective, there has been substantial interest in on the role of risk-perception on consumer behavior. Specific 'problem music' like rap and heavy metal has long been associated with delinquent behavior, including violence, drug use, and promiscuous sex. Although individuals' risk preferences have been investigated across a range of decision-making situations, there has been little empirical work demonstrating the direct role music may have on the likelihood of engaging in risky activities. In the exploratory study reported here, we assessed the impact of listening to different styles of music while assessing risk-taking likelihood through a psychometric scale. Risk-taking likelihood was measured across ethical, financial, health and safety, recreational and social domains. Through the means of a canonical correlation analysis, the multivariate relationship between different music styles and individual risk-taking likelihood across the different domains is discussed. Our results indicate that listening to different types of music does influence risk-taking likelihood, though not in areas of health and safety.

Vacua of maximal gauged D=3 supergravities

International Nuclear Information System (INIS)

Fischbacher, T; Nicolai, H; Samtleben, H

2002-01-01

We analyse the scalar potentials of maximal gauged three-dimensional supergravities which reveal a surprisingly rich structure. In contrast to maximal supergravities in dimensions D≥4, all these theories possess a maximally supersymmetric (N=16) ground state with negative cosmological constant Λ 2 gauged theory, whose maximally supersymmetric groundstate has Λ = 0. We compute the mass spectra of bosonic and fermionic fluctuations around these vacua and identify the unitary irreducible representations of the relevant background (super)isometry groups to which they belong. In addition, we find several stationary points which are not maximally supersymmetric, and determine their complete mass spectra as well. In particular, we show that there are analogues of all stationary points found in higher dimensions, among them are de Sitter (dS) vacua in the theories with noncompact gauge groups SO(5, 3) 2 and SO(4, 4) 2 , as well as anti-de Sitter (AdS) vacua in the compact gauged theory preserving 1/4 and 1/8 of the supersymmetries. All the dS vacua have tachyonic instabilities, whereas there do exist nonsupersymmetric AdS vacua which are stable, again in contrast to the D≥4 theories

Maximal muscular vascular conductances during whole body upright exercise in humans

Science.gov (United States)

Calbet, J A L; Jensen-Urstad, M; van Hall, G; Holmberg, H -C; Rosdahl, H; Saltin, B

2004-01-01

That muscular blood flow may reach 2.5 l kg−1 min−1 in the quadriceps muscle has led to the suggestion that muscular vascular conductance must be restrained during whole body exercise to avoid hypotension. The main aim of this study was to determine the maximal arm and leg muscle vascular conductances (VC) during leg and arm exercise, to find out if the maximal muscular vasodilatory response is restrained during maximal combined arm and leg exercise. Six Swedish elite cross-country skiers, age (mean ± s.e.m.) 24 ± 2 years, height 180 ± 2 cm, weight 74 ± 2 kg, and maximal oxygen uptake (V̇O2,max) 5.1 ± 0.1 l min−1 participated in the study. Femoral and subclavian vein blood flows, intra-arterial blood pressure, cardiac output, as well as blood gases in the femoral and subclavian vein, right atrium and femoral artery were determined during skiing (roller skis) at ∼76% of V̇O2,max and at V̇O2,max with different techniques: diagonal stride (combined arm and leg exercise), double poling (predominantly arm exercise) and leg skiing (predominantly leg exercise). During submaximal exercise cardiac output (26–27 l min−1), mean blood pressure (MAP) (∼87 mmHg), systemic VC, systemic oxygen delivery and pulmonary V̇O2 (∼4 l min−1) attained similar values regardless of exercise mode. The distribution of cardiac output was modified depending on the musculature engaged in the exercise. There was a close relationship between VC and V̇O2 in arms (r = 0.99, P arm VC (63.7 ± 5.6 ml min−1 mmHg−1) was attained during double poling, while peak leg VC was reached at maximal exercise with the diagonal technique (109.8 ± 11.5 ml min−1 mmHg−1) when arm VC was 38.8 ± 5.7 ml min−1 mmHg−1. If during maximal exercise arms and legs had been vasodilated to the observed maximal levels then mean arterial pressure would have dropped at least to 75–77 mmHg in our experimental conditions. It is concluded that skeletal muscle vascular conductance is

Assessing compatibility of direct detection data: halo-independent global likelihood analyses

Energy Technology Data Exchange (ETDEWEB)

Gelmini, Graciela B. [Department of Physics and Astronomy, UCLA,475 Portola Plaza, Los Angeles, CA 90095 (United States); Huh, Ji-Haeng [CERN Theory Division,CH-1211, Geneva 23 (Switzerland); Witte, Samuel J. [Department of Physics and Astronomy, UCLA,475 Portola Plaza, Los Angeles, CA 90095 (United States)

2016-10-18

We present two different halo-independent methods to assess the compatibility of several direct dark matter detection data sets for a given dark matter model using a global likelihood consisting of at least one extended likelihood and an arbitrary number of Gaussian or Poisson likelihoods. In the first method we find the global best fit halo function (we prove that it is a unique piecewise constant function with a number of down steps smaller than or equal to a maximum number that we compute) and construct a two-sided pointwise confidence band at any desired confidence level, which can then be compared with those derived from the extended likelihood alone to assess the joint compatibility of the data. In the second method we define a “constrained parameter goodness-of-fit” test statistic, whose p-value we then use to define a “plausibility region” (e.g. where p≥10%). For any halo function not entirely contained within the plausibility region, the level of compatibility of the data is very low (e.g. p<10%). We illustrate these methods by applying them to CDMS-II-Si and SuperCDMS data, assuming dark matter particles with elastic spin-independent isospin-conserving interactions or exothermic spin-independent isospin-violating interactions.

Imagination perspective affects ratings of the likelihood of occurrence of autobiographical memories.

Science.gov (United States)

Marsh, Benjamin U; Pezdek, Kathy; Lam, Shirley T

2014-07-01

Two experiments tested and confirmed the hypothesis that when the phenomenological characteristics of imagined events are more similar to those of related autobiographical memories, the imagined event is more likely to be considered to have occurred. At Time 1 and 2-weeks later, individuals rated the likelihood of occurrence for 20 life events. In Experiment 1, 1-week after Time 1, individuals imagined 3 childhood events from a first-person or third-person perspective. There was a no-imagination control. An increase in likelihood ratings from Time 1 to Time 2 resulted when imagination was from the third-person but not first-person perspective. In Experiment 2, childhood and recent events were imagined from a third- or first-person perspective. A significant interaction resulted. For childhood events, likelihood change scores were greater for third-person than first-person perspective; for recent adult events, likelihood change scores were greater for first-person than third-person perspective, although this latter trend was not significant. Copyright © 2014 Elsevier B.V. All rights reserved.

ldr: An R Software Package for Likelihood-Based Su?cient Dimension Reduction

Directory of Open Access Journals (Sweden)

Kofi Placid Adragni

2014-11-01

Full Text Available In regression settings, a su?cient dimension reduction (SDR method seeks the core information in a p-vector predictor that completely captures its relationship with a response. The reduced predictor may reside in a lower dimension d < p, improving ability to visualize data and predict future observations, and mitigating dimensionality issues when carrying out further analysis. We introduce ldr, a new R software package that implements three recently proposed likelihood-based methods for SDR: covariance reduction, likelihood acquired directions, and principal fitted components. All three methods reduce the dimensionality of the data by pro jection into lower dimensional subspaces. The package also implements a variable screening method built upon principal ?tted components which makes use of ?exible basis functions to capture the dependencies between the predictors and the response. Examples are given to demonstrate likelihood-based SDR analyses using ldr, including estimation of the dimension of reduction subspaces and selection of basis functions. The ldr package provides a framework that we hope to grow into a comprehensive library of likelihood-based SDR methodologies.

Use of deterministic sampling for exploring likelihoods in linkage analysis for quantitative traits.

NARCIS (Netherlands)

Mackinnon, M.J.; Beek, van der S.; Kinghorn, B.P.

1996-01-01

Deterministic sampling was used to numerically evaluate the expected log-likelihood surfaces of QTL-marker linkage models in large pedigrees with simple structures. By calculating the expected values of likelihoods, questions of power of experimental designs, bias in parameter estimates, approximate

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)

Detecting the contagion effect in mass killings; a constructive example of the statistical advantages of unbinned likelihood methods.

Science.gov (United States)

Towers, Sherry; Mubayi, Anuj; Castillo-Chavez, Carlos

2018-01-01

to analysis reproducibility and robustness. When an analysis cannot distinguish between a null and alternate hypothesis, care must be taken to ensure that the analysis methodology itself maximizes the use of information in the data that can distinguish between the two hypotheses. The use of binned methods by Lankford & Tomek (2017), that examined how many mass killings fell within a 14 day window from a previous mass killing, substantially reduced the sensitivity of their analysis to contagion effects. The unbinned likelihood methods used by Towers et al (2015) did not suffer from this problem. While a binned analysis might be favorable for simplicity and clarity of presentation, unbinned likelihood methods are preferable when effects might be somewhat subtle.

Caching and interpolated likelihoods: accelerating cosmological Monte Carlo Markov chains

Energy Technology Data Exchange (ETDEWEB)

Bouland, Adam; Easther, Richard; Rosenfeld, Katherine, E-mail: adam.bouland@aya.yale.edu, E-mail: richard.easther@yale.edu, E-mail: krosenfeld@cfa.harvard.edu [Department of Physics, Yale University, New Haven CT 06520 (United States)

2011-05-01

We describe a novel approach to accelerating Monte Carlo Markov Chains. Our focus is cosmological parameter estimation, but the algorithm is applicable to any problem for which the likelihood surface is a smooth function of the free parameters and computationally expensive to evaluate. We generate a high-order interpolating polynomial for the log-likelihood using the first points gathered by the Markov chains as a training set. This polynomial then accurately computes the majority of the likelihoods needed in the latter parts of the chains. We implement a simple version of this algorithm as a patch (InterpMC) to CosmoMC and show that it accelerates parameter estimatation by a factor of between two and four for well-converged chains. The current code is primarily intended as a ''proof of concept'', and we argue that there is considerable room for further performance gains. Unlike other approaches to accelerating parameter fits, we make no use of precomputed training sets or special choices of variables, and InterpMC is almost entirely transparent to the user.

Caching and interpolated likelihoods: accelerating cosmological Monte Carlo Markov chains

International Nuclear Information System (INIS)

Bouland, Adam; Easther, Richard; Rosenfeld, Katherine

2011-01-01

We describe a novel approach to accelerating Monte Carlo Markov Chains. Our focus is cosmological parameter estimation, but the algorithm is applicable to any problem for which the likelihood surface is a smooth function of the free parameters and computationally expensive to evaluate. We generate a high-order interpolating polynomial for the log-likelihood using the first points gathered by the Markov chains as a training set. This polynomial then accurately computes the majority of the likelihoods needed in the latter parts of the chains. We implement a simple version of this algorithm as a patch (InterpMC) to CosmoMC and show that it accelerates parameter estimatation by a factor of between two and four for well-converged chains. The current code is primarily intended as a ''proof of concept'', and we argue that there is considerable room for further performance gains. Unlike other approaches to accelerating parameter fits, we make no use of precomputed training sets or special choices of variables, and InterpMC is almost entirely transparent to the user

Sex differences in autonomic function following maximal exercise.

Science.gov (United States)

Kappus, Rebecca M; Ranadive, Sushant M; Yan, Huimin; Lane-Cordova, Abbi D; Cook, Marc D; Sun, Peng; Harvey, I Shevon; Wilund, Kenneth R; Woods, Jeffrey A; Fernhall, Bo

2015-01-01

Heart rate variability (HRV), blood pressure variability, (BPV) and heart rate recovery (HRR) are measures that provide insight regarding autonomic function. Maximal exercise can affect autonomic function, and it is unknown if there are sex differences in autonomic recovery following exercise. Therefore, the purpose of this study was to determine sex differences in several measures of autonomic function and the response following maximal exercise. Seventy-one (31 males and 40 females) healthy, nonsmoking, sedentary normotensive subjects between the ages of 18 and 35 underwent measurements of HRV and BPV at rest and following a maximal exercise bout. HRR was measured at minute one and two following maximal exercise. Males have significantly greater HRR following maximal exercise at both minute one and two; however, the significance between sexes was eliminated when controlling for VO2 peak. Males had significantly higher resting BPV-low-frequency (LF) values compared to females and did not significantly change following exercise, whereas females had significantly increased BPV-LF values following acute maximal exercise. Although males and females exhibited a significant decrease in both HRV-LF and HRV-high frequency (HF) with exercise, females had significantly higher HRV-HF values following exercise. Males had a significantly higher HRV-LF/HF ratio at rest; however, both males and females significantly increased their HRV-LF/HF ratio following exercise. Pre-menopausal females exhibit a cardioprotective autonomic profile compared to age-matched males due to lower resting sympathetic activity and faster vagal reactivation following maximal exercise. Acute maximal exercise is a sufficient autonomic stressor to demonstrate sex differences in the critical post-exercise recovery period.

Association of Adverse Childhood Experiences with Co-occurring Health Conditions in Early Childhood.

Science.gov (United States)

Bright, Melissa A; Thompson, Lindsay A

2018-01-01

To understand how adverse childhood experiences (ACEs) are associated with co-occurring physical, mental and developmental problems during early childhood. A subsample of 19,957 children aged 2-5 years were selected from the 2011-2012 National Survey for Child Health. Outcomes included 18 health conditions organized in singular condition domains (physical, mental, and developmental), and combinations of condition domains (e.g., physical plus mental, mental plus developmental, etc.). Predictors included 8 ACEs (divorce of a parent, death of a parent, exposure to domestic violence, living with someone with a drug or alcohol abuse problem, household member with a mental illness, parent incarceration, neighborhood violence, discrimination). Multivariable logistic regression was performed controlling for demographic characteristics, having a personal doctor, health insurance coverage, and seeing a health care professional in the previous year. Experiencing 3 or more ACEs before the age of 5 years was associated with increased likelihood of nearly every co-occurring condition combination across 3 domains of health. Most notably, experiencing 3 or more ACEs was also associated with a 2-fold increase in likelihood of having ≥1 physical condition and ≥1 developmental condition, a 9-fold increase in likelihood of having ≥1 mental and ≥1 developmental condition, and a 7-fold increase in likelihood of having ≥1 physical, ≥1 mental, and ≥1 developmental condition. This study demonstrates that we can identify the health effects of adversity quite early in development and that management should include communication between both health care and early childhood education providers.

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

Likelihood estimators for multivariate extremes

KAUST Repository

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

KAUST Repository

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.

Eccentric exercise decreases maximal insulin action in humans

DEFF Research Database (Denmark)

Asp, Svend; Daugaard, J R; Kristiansen, S

1996-01-01

subjects participated in two euglycaemic clamps, performed in random order. One clamp was preceded 2 days earlier by one-legged eccentric exercise (post-eccentric exercise clamp (PEC)) and one was without the prior exercise (control clamp (CC)). 2. During PEC the maximal insulin-stimulated glucose uptake...... for all three clamp steps used (P maximal activity of glycogen synthase was identical in the two thighs for all clamp steps. 3. The glucose infusion rate (GIR......) necessary to maintain euglycaemia during maximal insulin stimulation was lower during PEC compared with CC (15.7%, 81.3 +/- 3.2 vs. 96.4 +/- 8.8 mumol kg-1 min-1, P maximal...

Design of simplified maximum-likelihood receivers for multiuser CPM systems.

Science.gov (United States)

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.

A mixture of "cheats" and "co-operators" can enable maximal group benefit.

Directory of Open Access Journals (Sweden)

R Craig MaClean

Full Text Available Is a group best off if everyone co-operates? Theory often considers this to be so (e.g. the "conspiracy of doves", this understanding underpinning social and economic policy. We observe, however, that after competition between "cheat" and "co-operator" strains of yeast, population fitness is maximized under co-existence. To address whether this might just be a peculiarity of our experimental system or a result with broader applicability, we assemble, benchmark, dissect, and test a systems model. This reveals the conditions necessary to recover the unexpected result. These are 3-fold: (a that resources are used inefficiently when they are abundant, (b that the amount of co-operation needed cannot be accurately assessed, and (c the population is structured, such that co-operators receive more of the resource than the cheats. Relaxing any of the assumptions can lead to population fitness being maximized when cheats are absent, which we experimentally demonstrate. These three conditions will often be relevant, and hence in order to understand the trajectory of social interactions, understanding the dynamics of the efficiency of resource utilization and accuracy of information will be necessary.

Assessing Individual Weather Risk-Taking and Its Role in Modeling Likelihood of Hurricane Evacuation

Science.gov (United States)

Stewart, A. E.

2017-12-01

This research focuses upon measuring an individual's level of perceived risk of different severe and extreme weather conditions using a new self-report measure, the Weather Risk-Taking Scale (WRTS). For 32 severe and extreme situations in which people could perform an unsafe behavior (e. g., remaining outside with lightning striking close by, driving over roadways covered with water, not evacuating ahead of an approaching hurricane, etc.), people rated: 1.their likelihood of performing the behavior, 2. The perceived risk of performing the behavior, 3. the expected benefits of performing the behavior, and 4. whether the behavior has actually been performed in the past. Initial development research with the measure using 246 undergraduate students examined its psychometric properties and found that it was internally consistent (Cronbach's a ranged from .87 to .93 for the four scales) and that the scales possessed good temporal (test-retest) reliability (r's ranged from .84 to .91). A second regression study involving 86 undergraduate students found that taking weather risks was associated with having taken similar risks in one's past and with the personality trait of sensation-seeking. Being more attentive to the weather and perceiving its risks when it became extreme was associated with lower likelihoods of taking weather risks (overall regression model, R2adj = 0.60). A third study involving 334 people examined the contributions of weather risk perceptions and risk-taking in modeling the self-reported likelihood of complying with a recommended evacuation ahead of a hurricane. Here, higher perceptions of hurricane risks and lower perceived benefits of risk-taking along with fear of severe weather and hurricane personal self-efficacy ratings were all statistically significant contributors to the likelihood of evacuating ahead of a hurricane. Psychological rootedness and attachment to one's home also tend to predict lack of evacuation. This research highlights the

A Walk on the Wild Side: The Impact of Music on Risk-Taking Likelihood

Science.gov (United States)

Enström, Rickard; Schmaltz, Rodney

2017-01-01

From a marketing perspective, there has been substantial interest in on the role of risk-perception on consumer behavior. Specific ‘problem music’ like rap and heavy metal has long been associated with delinquent behavior, including violence, drug use, and promiscuous sex. Although individuals’ risk preferences have been investigated across a range of decision-making situations, there has been little empirical work demonstrating the direct role music may have on the likelihood of engaging in risky activities. In the exploratory study reported here, we assessed the impact of listening to different styles of music while assessing risk-taking likelihood through a psychometric scale. Risk-taking likelihood was measured across ethical, financial, health and safety, recreational and social domains. Through the means of a canonical correlation analysis, the multivariate relationship between different music styles and individual risk-taking likelihood across the different domains is discussed. Our results indicate that listening to different types of music does influence risk-taking likelihood, though not in areas of health and safety. PMID:28539908

A Walk on the Wild Side: The Impact of Music on Risk-Taking Likelihood

Directory of Open Access Journals (Sweden)

Rickard Enström

2017-05-01

Full Text Available From a marketing perspective, there has been substantial interest in on the role of risk-perception on consumer behavior. Specific ‘problem music’ like rap and heavy metal has long been associated with delinquent behavior, including violence, drug use, and promiscuous sex. Although individuals’ risk preferences have been investigated across a range of decision-making situations, there has been little empirical work demonstrating the direct role music may have on the likelihood of engaging in risky activities. In the exploratory study reported here, we assessed the impact of listening to different styles of music while assessing risk-taking likelihood through a psychometric scale. Risk-taking likelihood was measured across ethical, financial, health and safety, recreational and social domains. Through the means of a canonical correlation analysis, the multivariate relationship between different music styles and individual risk-taking likelihood across the different domains is discussed. Our results indicate that listening to different types of music does influence risk-taking likelihood, though not in areas of health and safety.

Optimization of Second Fault Detection Thresholds to Maximize Mission POS

Science.gov (United States)

Anzalone, Evan

2018-01-01

both magnitude and time. As such, the Navigation team is taking advantage of the INS's capability to schedule and change fault detection thresholds in flight. These values are optimized along a nominal trajectory in order to maximize probability of mission success, and reducing the probability of false positives (defined as when the INS would report a second fault condition resulting in loss of mission, but the vehicle would still meet insertion requirements within system-level margins). This paper will describe an optimization approach using Genetic Algorithms to tune the threshold parameters to maximize vehicle resilience to second fault events as a function of potential fault magnitude and time of fault over an ascent mission profile. The analysis approach, and performance assessment of the results will be presented to demonstrate the applicability of this process to second fault detection to maximize mission probability of success.

Hyperventilation-induced respiratory alkalosis falls short of countering fatigue during repeated maximal isokinetic contractions.

Science.gov (United States)

Sakamoto, Akihiro; Naito, Hisashi; Chow, Chin Moi

2015-07-01

Hyperventilation, implemented during recovery of repeated maximal sprints, has been shown to attenuate performance decrement. This study evaluated the effects of hyperventilation, using strength exercises, on muscle torque output and EMG amplitude. Fifteen power-trained athletes underwent maximal isokinetic knee extensions consisting of 12 repetitions × 8 sets at 60°/s and 25 repetitions × 8 sets at 300°/s. The inter-set interval was 40 s for both speeds. For the control condition, subjects breathed spontaneously during the interval period. For the hyperventilation condition, subjects hyperventilated for 30 s before each exercise set (50 breaths/min, PETCO2: 20-25 mmHg). EMG was recorded from the vastus medialis and lateralis muscles to calculate the mean amplitude for each contraction. Hyperventilation increased blood pH by 0.065-0.081 and lowered PCO2 by 8.3-10.3 mmHg from the control values (P < 0.001). Peak torque declined with repetition and set numbers for both speeds (P < 0.001), but the declining patterns were similar between conditions. A significant, but small enhancement in peak torque was observed with hyperventilation at 60°/s during the initial repetition phase of the first (P = 0.032) and fourth sets (P = 0.040). EMG amplitude also declined with set number (P < 0.001) for both speeds and muscles, which was, however, not attenuated by hyperventilation. Despite a minor ergogenic effect in peak torque at 60°/s, hyperventilation was not effective in attenuating the decrement in torque output at 300°/s and decrement in EMG amplitude at both speeds during repeated sets of maximal isokinetic knee extensions.

Likelihood-based inference for clustered line transect data

DEFF Research Database (Denmark)

Waagepetersen, Rasmus Plenge; Schweder, Tore

The uncertainty in estimation of spatial animal density from line transect surveys depends on the degree of spatial clustering in the animal population. To quantify the clustering we model line transect data as independent thinnings of spatial shot-noise Cox processes. Likelihood-based inference...

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...

Likelihood-based inference for clustered line transect data

DEFF Research Database (Denmark)

Waagepetersen, Rasmus; Schweder, Tore

2006-01-01

The uncertainty in estimation of spatial animal density from line transect surveys depends on the degree of spatial clustering in the animal population. To quantify the clustering we model line transect data as independent thinnings of spatial shot-noise Cox processes. Likelihood-based inference...

Genus one super-Green function revisited and superstring amplitudes with non-maximal supersymmetry

International Nuclear Information System (INIS)

Itoyama, H.; Yano, Kohei

2016-01-01

We reexamine genus one super-Green functions with general boundary conditions twisted by (α,β) for (σ,τ) directions in the eigenmode expansion and derive expressions as infinite series of hypergeometric functions. Using these, we compute one-loop superstring amplitudes with non-maximal supersymmetry, taking the example of massless vector emissions of open string type I Z 2 orbifold

Fast maximum likelihood estimation of mutation rates using a birth-death process.

Science.gov (United States)

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.

Utility Maximization in Nonconvex Wireless Systems

CERN Document Server

Brehmer, Johannes

2012-01-01

This monograph formulates a framework for modeling and solving utility maximization problems in nonconvex wireless systems. First, a model for utility optimization in wireless systems is defined. The model is general enough to encompass a wide array of system configurations and performance objectives. Based on the general model, a set of methods for solving utility maximization problems is developed. The development is based on a careful examination of the properties that are required for the application of each method. The focus is on problems whose initial formulation does not allow for a solution by standard convex methods. Solution approaches that take into account the nonconvexities inherent to wireless systems are discussed in detail. The monograph concludes with two case studies that demonstrate the application of the proposed framework to utility maximization in multi-antenna broadcast channels.

Market conditions and hedge fund survival

OpenAIRE

Mark A. Carlson; Jason Steinman

2008-01-01

As the hedge fund industry has grown, there has been increased concern that, during sharp market moves, hedge fund failures could exacerbate the deterioration in financial conditions and deepen a crisis. However, there has not been much formal analysis regarding the impact of financial market conditions on hedge fund survival. To help fill this gap, this paper examines the relationship between financial market conditions and the likelihood of hedge fund failure after controlling for performan...

Likelihood ratio data to report the validation of a forensic fingerprint evaluation method

NARCIS (Netherlands)

Ramos, Daniel; Haraksim, Rudolf; Meuwly, Didier

2017-01-01

Data to which the authors refer to throughout this article are likelihood ratios (LR) computed from the comparison of 5–12 minutiae fingermarks with fingerprints. These LRs data are used for the validation of a likelihood ratio (LR) method in forensic evidence evaluation. These data present a

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...

Tight upper bound for the maximal quantum value of the Svetlichny operators

Science.gov (United States)

Li, Ming; Shen, Shuqian; Jing, Naihuan; Fei, Shao-Ming; Li-Jost, Xianqing

2017-10-01

It is a challenging task to detect genuine multipartite nonlocality (GMNL). In this paper, the problem is considered via computing the maximal quantum value of Svetlichny operators for three-qubit systems and a tight upper bound is obtained. The constraints on the quantum states for the tightness of the bound are also presented. The approach enables us to give the necessary and sufficient conditions of violating the Svetlichny inequality (SI) for several quantum states, including the white and color noised Greenberger-Horne-Zeilinger (GHZ) states. The relation between the genuine multipartite entanglement concurrence and the maximal quantum value of the Svetlichny operators for mixed GHZ class states is also discussed. As the SI is useful for the investigation of GMNL, our results give an effective and operational method to detect the GMNL for three-qubit mixed states.

Aging and loss decision making: increased risk aversion and decreased use of maximizing information, with correlated rationality and value maximization.

Science.gov (United States)

Kurnianingsih, Yoanna A; Sim, Sam K Y; Chee, Michael W L; Mullette-Gillman, O'Dhaniel A

2015-01-01

We investigated how adult aging specifically alters economic decision-making, focusing on examining alterations in uncertainty preferences (willingness to gamble) and choice strategies (what gamble information influences choices) within both the gains and losses domains. Within each domain, participants chose between certain monetary outcomes and gambles with uncertain outcomes. We examined preferences by quantifying how uncertainty modulates choice behavior as if altering the subjective valuation of gambles. We explored age-related preferences for two types of uncertainty, risk, and ambiguity. Additionally, we explored how aging may alter what information participants utilize to make their choices by comparing the relative utilization of maximizing and satisficing information types through a choice strategy metric. Maximizing information was the ratio of the expected value of the two options, while satisficing information was the probability of winning. We found age-related alterations of economic preferences within the losses domain, but no alterations within the gains domain. Older adults (OA; 61-80 years old) were significantly more uncertainty averse for both risky and ambiguous choices. OA also exhibited choice strategies with decreased use of maximizing information. Within OA, we found a significant correlation between risk preferences and choice strategy. This linkage between preferences and strategy appears to derive from a convergence to risk neutrality driven by greater use of the effortful maximizing strategy. As utility maximization and value maximization intersect at risk neutrality, this result suggests that OA are exhibiting a relationship between enhanced rationality and enhanced value maximization. While there was variability in economic decision-making measures within OA, these individual differences were unrelated to variability within examined measures of cognitive ability. Our results demonstrate that aging alters economic decision-making for

Aging and loss decision making: increased risk aversion and decreased use of maximizing information, with correlated rationality and value maximization

Directory of Open Access Journals (Sweden)

Yoanna Arlina Kurnianingsih

2015-05-01

Full Text Available We investigated how adult aging specifically alters economic decision-making, focusing on examining alterations in uncertainty preferences (willingness to gamble and choice strategies (what gamble information influences choices within both the gains and losses domains. Within each domain, participants chose between certain monetary outcomes and gambles with uncertain outcomes. We examined preferences by quantifying how uncertainty modulates choice behavior as if altering the subjective valuation of gambles. We explored age-related preferences for two types of uncertainty, risk and ambiguity. Additionally, we explored how aging may alter what information participants utilize to make their choices by comparing the relative utilization of maximizing and satisficing information types through a choice strategy metric. Maximizing information was the ratio of the expected value of the two options, while satisficing information was the probability of winning.We found age-related alterations of economic preferences within the losses domain, but no alterations within the gains domain. Older adults (OA; 61 to 80 years old were significantly more uncertainty averse for both risky and ambiguous choices. OA also exhibited choice strategies with decreased use of maximizing information. Within OA, we found a significant correlation between risk preferences and choice strategy. This linkage between preferences and strategy appears to derive from a convergence to risk neutrality driven by greater use of the effortful maximizing strategy. As utility maximization and value maximization intersect at risk neutrality, this result suggests that OA are exhibiting a relationship between enhanced rationality and enhanced value maximization. While there was variability in economic decision-making measures within OA, these individual differences were unrelated to variability within examined measures of cognitive ability. Our results demonstrate that aging alters economic

Exact sampling from conditional Boolean models with applications to maximum likelihood inference

NARCIS (Netherlands)

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

Quasi-Maximum Likelihood Estimation and Bootstrap Inference in Fractional Time Series Models with Heteroskedasticity of Unknown Form

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...

Block Empirical Likelihood for Longitudinal Single-Index Varying-Coefficient Model

Directory of Open Access Journals (Sweden)

Yunquan Song

2013-01-01

Full Text Available In this paper, we consider a single-index varying-coefficient model with application to longitudinal data. In order to accommodate the within-group correlation, we apply the block empirical likelihood procedure to longitudinal single-index varying-coefficient model, and prove a nonparametric version of Wilks’ theorem which can be used to construct the block empirical likelihood confidence region with asymptotically correct coverage probability for the parametric component. In comparison with normal approximations, the proposed method does not require a consistent estimator for the asymptotic covariance matrix, making it easier to conduct inference for the model's parametric component. Simulations demonstrate how the proposed method works.

Design of Simplified Maximum-Likelihood Receivers for Multiuser CPM Systems

Directory of Open Access Journals (Sweden)

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.

Non-negative matrix factorization by maximizing correntropy for cancer clustering

KAUST Repository

Wang, Jim Jing-Yan; Wang, Xiaolei; Gao, Xin

2013-01-01

Background: Non-negative matrix factorization (NMF) has been shown to be a powerful tool for clustering gene expression data, which are widely used to classify cancers. NMF aims to find two non-negative matrices whose product closely approximates the original matrix. Traditional NMF methods minimize either the l2 norm or the Kullback-Leibler distance between the product of the two matrices and the original matrix. Correntropy was recently shown to be an effective similarity measurement due to its stability to outliers or noise.Results: We propose a maximum correntropy criterion (MCC)-based NMF method (NMF-MCC) for gene expression data-based cancer clustering. Instead of minimizing the l2 norm or the Kullback-Leibler distance, NMF-MCC maximizes the correntropy between the product of the two matrices and the original matrix. The optimization problem can be solved by an expectation conditional maximization algorithm.Conclusions: Extensive experiments on six cancer benchmark sets demonstrate that the proposed method is significantly more accurate than the state-of-the-art methods in cancer clustering. 2013 Wang et al.; licensee BioMed Central Ltd.

Non-negative matrix factorization by maximizing correntropy for cancer clustering

KAUST Repository

Wang, Jim Jing-Yan

2013-03-24

Background: Non-negative matrix factorization (NMF) has been shown to be a powerful tool for clustering gene expression data, which are widely used to classify cancers. NMF aims to find two non-negative matrices whose product closely approximates the original matrix. Traditional NMF methods minimize either the l2 norm or the Kullback-Leibler distance between the product of the two matrices and the original matrix. Correntropy was recently shown to be an effective similarity measurement due to its stability to outliers or noise.Results: We propose a maximum correntropy criterion (MCC)-based NMF method (NMF-MCC) for gene expression data-based cancer clustering. Instead of minimizing the l2 norm or the Kullback-Leibler distance, NMF-MCC maximizes the correntropy between the product of the two matrices and the original matrix. The optimization problem can be solved by an expectation conditional maximization algorithm.Conclusions: Extensive experiments on six cancer benchmark sets demonstrate that the proposed method is significantly more accurate than the state-of-the-art methods in cancer clustering. 2013 Wang et al.; licensee BioMed Central Ltd.

Attitude towards, and likelihood of, complaining in the banking ...

African Journals Online (AJOL)

aims to determine customers' attitudes towards complaining as well as their likelihood of voicing a .... is particularly powerful and impacts greatly on customer satisfaction and retention. ...... 'Cross-national analysis of hotel customers' attitudes ...

Physical constraints on the likelihood of life on exoplanets

Science.gov (United States)

Lingam, Manasvi; Loeb, Abraham

2018-04-01

One of the most fundamental questions in exoplanetology is to determine whether a given planet is habitable. We estimate the relative likelihood of a planet's propensity towards habitability by considering key physical characteristics such as the role of temperature on ecological and evolutionary processes, and atmospheric losses via hydrodynamic escape and stellar wind erosion. From our analysis, we demonstrate that Earth-sized exoplanets in the habitable zone around M-dwarfs seemingly display much lower prospects of being habitable relative to Earth, owing to the higher incident ultraviolet fluxes and closer distances to the host star. We illustrate our results by specifically computing the likelihood (of supporting life) for the recently discovered exoplanets, Proxima b and TRAPPIST-1e, which we find to be several orders of magnitude smaller than that of Earth.

Maximally Informative Observables and Categorical Perception

OpenAIRE

Tsiang, Elaine

2012-01-01

We formulate the problem of perception in the framework of information theory, and prove that categorical perception is equivalent to the existence of an observable that has the maximum possible information on the target of perception. We call such an observable maximally informative. Regardless whether categorical perception is real, maximally informative observables can form the basis of a theory of perception. We conclude with the implications of such a theory for the problem of speech per...

Maximally Entangled Multipartite States: A Brief Survey

International Nuclear Information System (INIS)

Enríquez, M; Wintrowicz, I; Życzkowski, K

2016-01-01

The problem of identifying maximally entangled quantum states of a composite quantum systems is analyzed. We review some states of multipartite systems distinguished with respect to certain measures of quantum entanglement. Numerical results obtained for 4-qubit pure states illustrate the fact that the notion of maximally entangled state depends on the measure used. (paper)

Validation of DNA-based identification software by computation of pedigree likelihood ratios.

Science.gov (United States)

Slooten, K

2011-08-01

Disaster victim identification (DVI) can be aided by DNA-evidence, by comparing the DNA-profiles of unidentified individuals with those of surviving relatives. The DNA-evidence is used optimally when such a comparison is done by calculating the appropriate likelihood ratios. Though conceptually simple, the calculations can be quite involved, especially with large pedigrees, precise mutation models etc. In this article we describe a series of test cases designed to check if software designed to calculate such likelihood ratios computes them correctly. The cases include both simple and more complicated pedigrees, among which inbred ones. We show how to calculate the likelihood ratio numerically and algebraically, including a general mutation model and possibility of allelic dropout. In Appendix A we show how to derive such algebraic expressions mathematically. We have set up these cases to validate new software, called Bonaparte, which performs pedigree likelihood ratio calculations in a DVI context. Bonaparte has been developed by SNN Nijmegen (The Netherlands) for the Netherlands Forensic Institute (NFI). It is available free of charge for non-commercial purposes (see www.dnadvi.nl for details). Commercial licenses can also be obtained. The software uses Bayesian networks and the junction tree algorithm to perform its calculations. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Guinea pig maximization test

DEFF Research Database (Denmark)

Andersen, Klaus Ejner

1985-01-01

Guinea pig maximization tests (GPMT) with chlorocresol were performed to ascertain whether the sensitization rate was affected by minor changes in the Freund's complete adjuvant (FCA) emulsion used. Three types of emulsion were evaluated: the oil phase was mixed with propylene glycol, saline...

Maximized Inter-Class Weighted Mean for Fast and Accurate Mitosis Cells Detection in Breast Cancer Histopathology Images.

Science.gov (United States)

Nateghi, Ramin; Danyali, Habibollah; Helfroush, Mohammad Sadegh

2017-08-14

Based on the Nottingham criteria, the number of mitosis cells in histopathological slides is an important factor in diagnosis and grading of breast cancer. For manual grading of mitosis cells, histopathology slides of the tissue are examined by pathologists at 40× magnification for each patient. This task is very difficult and time-consuming even for experts. In this paper, a fully automated method is presented for accurate detection of mitosis cells in histopathology slide images. First a method based on maximum-likelihood is employed for segmentation and extraction of mitosis cell. Then a novel Maximized Inter-class Weighted Mean (MIWM) method is proposed that aims at reducing the number of extracted non-mitosis candidates that results in reducing the false positive mitosis detection rate. Finally, segmented candidates are classified into mitosis and non-mitosis classes by using a support vector machine (SVM) classifier. Experimental results demonstrate a significant improvement in accuracy of mitosis cells detection in different grades of breast cancer histopathological images.

Global Convergence of the EM Algorithm for Unconstrained Latent Variable Models with Categorical Indicators

Science.gov (United States)

Weissman, Alexander

2013-01-01

Convergence of the expectation-maximization (EM) algorithm to a global optimum of the marginal log likelihood function for unconstrained latent variable models with categorical indicators is presented. The sufficient conditions under which global convergence of the EM algorithm is attainable are provided in an information-theoretic context by…

Collusion through price ceilings? In search of a focal-point effect

NARCIS (Netherlands)

Engelmann, D.; Müller, W.

2011-01-01

We resume the search for a collusive focal-point effect of price ceilings in laboratory markets. We argue that market conditions in previous studies were unfavorable for collusion which may have been responsible for not finding such a focal-point effect. Our design aims at maximizing the likelihood

Inquiry in bibliography some of the bustan`s maxim

Directory of Open Access Journals (Sweden)

sajjad rahmatian

2016-12-01

Full Text Available Sa`di is on of those poets who`s has placed a special position to preaching and guiding the people and among his works, allocated throughout the text of bustan to advice and maxim on legal and ethical various subjects. Surely, sa`di on the way of to compose this work and expression of its moral point, direct or indirect have been affected by some previous sources and possibly using their content. The main purpose of this article is that the pay review of basis and sources of bustan`s maxims and show that sa`di when expression the maxims of this work has been affected by which of the texts and works. For this purpose is tried to with search and research on the resources that have been allocated more or less to the aphorisms, to discover and extract traces of influence sa`di from their moral and didactic content. From the most important the finding of this study can be mentioned that indirect effect of some pahlavi books of maxim (like maxims of azarbad marespandan and bozorgmehr book of maxim and also noted sa`di directly influenced of moral and ethical works of poets and writers before him, and of this, sa`di`s influence from abo- shakur balkhi maxims, ferdowsi and keikavus is remarkable and noteworthy.

Can monkeys make investments based on maximized pay-off?

Directory of Open Access Journals (Sweden)

Sophie Steelandt

2011-03-01

Full Text Available Animals can maximize benefits but it is not known if they adjust their investment according to expected pay-offs. We investigated whether monkeys can use different investment strategies in an exchange task. We tested eight capuchin monkeys (Cebus apella and thirteen macaques (Macaca fascicularis, Macaca tonkeana in an experiment where they could adapt their investment to the food amounts proposed by two different experimenters. One, the doubling partner, returned a reward that was twice the amount given by the subject, whereas the other, the fixed partner, always returned a constant amount regardless of the amount given. To maximize pay-offs, subjects should invest a maximal amount with the first partner and a minimal amount with the second. When tested with the fixed partner only, one third of monkeys learned to remove a maximal amount of food for immediate consumption before investing a minimal one. With both partners, most subjects failed to maximize pay-offs by using different decision rules with each partner' quality. A single Tonkean macaque succeeded in investing a maximal amount to one experimenter and a minimal amount to the other. The fact that only one of over 21 subjects learned to maximize benefits in adapting investment according to experimenters' quality indicates that such a task is difficult for monkeys, albeit not impossible.

Maximal lattice free bodies, test sets and the Frobenius problem

DEFF Research Database (Denmark)

Jensen, Anders Nedergaard; Lauritzen, Niels; Roune, Bjarke Hammersholt

Maximal lattice free bodies are maximal polytopes without interior integral points. Scarf initiated the study of maximal lattice free bodies relative to the facet normals in a fixed matrix. In this paper we give an efficient algorithm for computing the maximal lattice free bodies of an integral m...... method is inspired by the novel algorithm by Einstein, Lichtblau, Strzebonski and Wagon and the Groebner basis approach by Roune....

Disk Density Tuning of a Maximal Random Packing.

Science.gov (United States)

Ebeida, Mohamed S; Rushdi, Ahmad A; Awad, Muhammad A; Mahmoud, Ahmed H; Yan, Dong-Ming; English, Shawn A; Owens, John D; Bajaj, Chandrajit L; Mitchell, Scott A

2016-08-01

We introduce an algorithmic framework for tuning the spatial density of disks in a maximal random packing, without changing the sizing function or radii of disks. Starting from any maximal random packing such as a Maximal Poisson-disk Sampling (MPS), we iteratively relocate, inject (add), or eject (remove) disks, using a set of three successively more-aggressive local operations. We may achieve a user-defined density, either more dense or more sparse, almost up to the theoretical structured limits. The tuned samples are conflict-free, retain coverage maximality, and, except in the extremes, retain the blue noise randomness properties of the input. We change the density of the packing one disk at a time, maintaining the minimum disk separation distance and the maximum domain coverage distance required of any maximal packing. These properties are local, and we can handle spatially-varying sizing functions. Using fewer points to satisfy a sizing function improves the efficiency of some applications. We apply the framework to improve the quality of meshes, removing non-obtuse angles; and to more accurately model fiber reinforced polymers for elastic and failure simulations.

An information maximization model of eye movements

Science.gov (United States)

Renninger, Laura Walker; Coughlan, James; Verghese, Preeti; Malik, Jitendra

2005-01-01

We propose a sequential information maximization model as a general strategy for programming eye movements. The model reconstructs high-resolution visual information from a sequence of fixations, taking into account the fall-off in resolution from the fovea to the periphery. From this framework we get a simple rule for predicting fixation sequences: after each fixation, fixate next at the location that minimizes uncertainty (maximizes information) about the stimulus. By comparing our model performance to human eye movement data and to predictions from a saliency and random model, we demonstrate that our model is best at predicting fixation locations. Modeling additional biological constraints will improve the prediction of fixation sequences. Our results suggest that information maximization is a useful principle for programming eye movements.

Superfast maximum-likelihood reconstruction for quantum tomography

Science.gov (United States)

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.

Comparisons of likelihood and machine learning methods of individual classification

Science.gov (United States)

Guinand, B.; Topchy, A.; Page, K.S.; Burnham-Curtis, M. K.; Punch, W.F.; Scribner, K.T.

2002-01-01

Classification methods used in machine learning (e.g., artificial neural networks, decision trees, and k-nearest neighbor clustering) are rarely used with population genetic data. We compare different nonparametric machine learning techniques with parametric likelihood estimations commonly employed in population genetics for purposes of assigning individuals to their population of origin (“assignment tests”). Classifier accuracy was compared across simulated data sets representing different levels of population differentiation (low and high FST), number of loci surveyed (5 and 10), and allelic diversity (average of three or eight alleles per locus). Empirical data for the lake trout (Salvelinus namaycush) exhibiting levels of population differentiation comparable to those used in simulations were examined to further evaluate and compare classification methods. Classification error rates associated with artificial neural networks and likelihood estimators were lower for simulated data sets compared to k-nearest neighbor and decision tree classifiers over the entire range of parameters considered. Artificial neural networks only marginally outperformed the likelihood method for simulated data (0–2.8% lower error rates). The relative performance of each machine learning classifier improved relative likelihood estimators for empirical data sets, suggesting an ability to “learn” and utilize properties of empirical genotypic arrays intrinsic to each population. Likelihood-based estimation methods provide a more accessible option for reliable assignment of individuals to the population of origin due to the intricacies in development and evaluation of artificial neural networks. In recent years, characterization of highly polymorphic molecular markers such as mini- and microsatellites and development of novel methods of analysis have enabled researchers to extend investigations of ecological and evolutionary processes below the population level to the level of

On the way towards a generalized entropy maximization procedure

International Nuclear Information System (INIS)

Bagci, G. Baris; Tirnakli, Ugur

2009-01-01

We propose a generalized entropy maximization procedure, which takes into account the generalized averaging procedures and information gain definitions underlying the generalized entropies. This novel generalized procedure is then applied to Renyi and Tsallis entropies. The generalized entropy maximization procedure for Renyi entropies results in the exponential stationary distribution asymptotically for q element of (0,1] in contrast to the stationary distribution of the inverse power law obtained through the ordinary entropy maximization procedure. Another result of the generalized entropy maximization procedure is that one can naturally obtain all the possible stationary distributions associated with the Tsallis entropies by employing either ordinary or q-generalized Fourier transforms in the averaging procedure.

Violating Bell inequalities maximally for two d-dimensional systems

International Nuclear Information System (INIS)

Chen Jingling; Wu Chunfeng; Oh, C. H.; Kwek, L. C.; Ge Molin

2006-01-01

We show the maximal violation of Bell inequalities for two d-dimensional systems by using the method of the Bell operator. The maximal violation corresponds to the maximal eigenvalue of the Bell operator matrix. The eigenvectors corresponding to these eigenvalues are described by asymmetric entangled states. We estimate the maximum value of the eigenvalue for large dimension. A family of elegant entangled states |Ψ> app that violate Bell inequality more strongly than the maximally entangled state but are somewhat close to these eigenvectors is presented. These approximate states can potentially be useful for quantum cryptography as well as many other important fields of quantum information

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...

Cosmic shear measurement with maximum likelihood and maximum a posteriori inference

Science.gov (United States)

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.

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...

The skewed weak lensing likelihood: why biases arise, despite data and theory being sound.

Science.gov (United States)

Sellentin, Elena; Heymans, Catherine; Harnois-Déraps, Joachim

2018-04-01

We derive the essentials of the skewed weak lensing likelihood via a simple Hierarchical Forward Model. Our likelihood passes four objective and cosmology-independent tests which a standard Gaussian likelihood fails. We demonstrate that sound weak lensing data are naturally biased low, since they are drawn from a skewed distribution. This occurs already in the framework of ΛCDM. Mathematically, the biases arise because noisy two-point functions follow skewed distributions. This form of bias is already known from CMB analyses, where the low multipoles have asymmetric error bars. Weak lensing is more strongly affected by this asymmetry as galaxies form a discrete set of shear tracer particles, in contrast to a smooth shear field. We demonstrate that the biases can be up to 30% of the standard deviation per data point, dependent on the properties of the weak lensing survey and the employed filter function. Our likelihood provides a versatile framework with which to address this bias in future weak lensing analyses.

Uncertain call likelihood negatively affects sleep and next-day cognitive performance while on-call in a laboratory environment.

Science.gov (United States)

Sprajcer, Madeline; Jay, Sarah M; Vincent, Grace E; Vakulin, Andrew; Lack, Leon; Ferguson, Sally A

2018-05-11

On-call working arrangements are employed in a number of industries to manage unpredictable events, and often involve tasks that are safety- or time-critical. This study investigated the effects of call likelihood during an overnight on-call shift on self-reported pre-bed anxiety, sleep and next-day cognitive performance. A four-night laboratory-based protocol was employed, with an adaptation, a control and two counterbalanced on-call nights. On one on-call night, participants were instructed that they would definitely be called during the night, while on the other on-call night they were told they may be called. The State-Trait Anxiety Inventory form x-1 was used to investigate pre-bed anxiety, and sleep was assessed using polysomnography and power spectral analysis of the sleep electroencephalographic analysis. Cognitive performance was assessed four times daily using a 10-min psychomotor vigilance task. Participants felt more anxious before bed when they were definitely going to be called, compared with the control and maybe conditions. Conversely, participants experienced significantly less non-rapid eye movement and stage two sleep and poorer cognitive performance when told they may be called. Further, participants had significantly more rapid eye movement sleep in the maybe condition, which may be an adaptive response to the stress associated with this on-call condition. It appears that self-reported anxiety may not be linked with sleep outcomes while on-call. However, this research indicates that it is important to take call likelihood into consideration when constructing rosters and risk-management systems for on-call workers.

Average Likelihood Methods of Classification of Code Division Multiple Access (CDMA)

Science.gov (United States)

2016-05-01

subject to code matrices that follows the structure given by (113). [⃗ yR y⃗I ] = √ Es 2L [ GR1 −GI1 GI2 GR2 ] [ QR −QI QI QR ] [⃗ bR b⃗I ] + [⃗ nR n⃗I... QR ] [⃗ b+ b⃗− ] + [⃗ n+ n⃗− ] (115) The average likelihood for type 4 CDMA (116) is a special case of type 1 CDMA with twice the code length and...AVERAGE LIKELIHOOD METHODS OF CLASSIFICATION OF CODE DIVISION MULTIPLE ACCESS (CDMA) MAY 2016 FINAL TECHNICAL REPORT APPROVED FOR PUBLIC RELEASE

Real-time topic-aware influence maximization using preprocessing.

Science.gov (United States)

Chen, Wei; Lin, Tian; Yang, Cheng

2016-01-01

Influence maximization is the task of finding a set of seed nodes in a social network such that the influence spread of these seed nodes based on certain influence diffusion model is maximized. Topic-aware influence diffusion models have been recently proposed to address the issue that influence between a pair of users are often topic-dependent and information, ideas, innovations etc. being propagated in networks are typically mixtures of topics. In this paper, we focus on the topic-aware influence maximization task. In particular, we study preprocessing methods to avoid redoing influence maximization for each mixture from scratch. We explore two preprocessing algorithms with theoretical justifications. Our empirical results on data obtained in a couple of existing studies demonstrate that one of our algorithms stands out as a strong candidate providing microsecond online response time and competitive influence spread, with reasonable preprocessing effort.

Review of Elaboration Likelihood Model of persuasion

OpenAIRE

藤原, 武弘; 神山, 貴弥

1989-01-01

This article mainly introduces Elaboration Likelihood Model (ELM), proposed by Petty & Cacioppo, that is, a general attitude change theory. ELM posturates two routes to persuasion; central and peripheral route. Attitude change by central route is viewed as resulting from a diligent consideration of the issue-relevant informations presented. On the other hand, attitude change by peripheral route is viewed as resulting from peripheral cues in the persuasion context. Secondly we compare these tw...

Validation of software for calculating the likelihood ratio for parentage and kinship.

Science.gov (United States)

Drábek, J

2009-03-01

Although the likelihood ratio is a well-known statistical technique, commercial off-the-shelf (COTS) software products for its calculation are not sufficiently validated to suit general requirements for the competence of testing and calibration laboratories (EN/ISO/IEC 17025:2005 norm) per se. The software in question can be considered critical as it directly weighs the forensic evidence allowing judges to decide on guilt or innocence or to identify person or kin (i.e.: in mass fatalities). For these reasons, accredited laboratories shall validate likelihood ratio software in accordance with the above norm. To validate software for calculating the likelihood ratio in parentage/kinship scenarios I assessed available vendors, chose two programs (Paternity Index and familias) for testing, and finally validated them using tests derived from elaboration of the available guidelines for the field of forensics, biomedicine, and software engineering. MS Excel calculation using known likelihood ratio formulas or peer-reviewed results of difficult paternity cases were used as a reference. Using seven testing cases, it was found that both programs satisfied the requirements for basic paternity cases. However, only a combination of two software programs fulfills the criteria needed for our purpose in the whole spectrum of functions under validation with the exceptions of providing algebraic formulas in cases of mutation and/or silent allele.

A guideline for the validation of likelihood ratio methods used for forensic evidence evaluation

NARCIS (Netherlands)

Meuwly, Didier; Ramos, Daniel; Haraksim, Rudolf

2017-01-01

This Guideline proposes a protocol for the validation of forensic evaluation methods at the source level, using the Likelihood Ratio framework as defined within the Bayes’ inference model. In the context of the inference of identity of source, the Likelihood Ratio is used to evaluate the strength of

Likelihood for transcriptions in a genetic regulatory system under asymmetric stable Lévy noise.

Science.gov (United States)

Wang, Hui; Cheng, Xiujun; Duan, Jinqiao; Kurths, Jürgen; Li, Xiaofan

2018-01-01

This work is devoted to investigating the evolution of concentration in a genetic regulation system, when the synthesis reaction rate is under additive and multiplicative asymmetric stable Lévy fluctuations. By focusing on the impact of skewness (i.e., non-symmetry) in the probability distributions of noise, we find that via examining the mean first exit time (MFET) and the first escape probability (FEP), the asymmetric fluctuations, interacting with nonlinearity in the system, lead to peculiar likelihood for transcription. This includes, in the additive noise case, realizing higher likelihood of transcription for larger positive skewness (i.e., asymmetry) index β, causing a stochastic bifurcation at the non-Gaussianity index value α = 1 (i.e., it is a separating point or line for the likelihood for transcription), and achieving a turning point at the threshold value β≈-0.5 (i.e., beyond which the likelihood for transcription suddenly reversed for α values). The stochastic bifurcation and turning point phenomena do not occur in the symmetric noise case (β = 0). While in the multiplicative noise case, non-Gaussianity index value α = 1 is a separating point or line for both the MFET and the FEP. We also investigate the noise enhanced stability phenomenon. Additionally, we are able to specify the regions in the whole parameter space for the asymmetric noise, in which we attain desired likelihood for transcription. We have conducted a series of numerical experiments in "regulating" the likelihood of gene transcription by tuning asymmetric stable Lévy noise indexes. This work offers insights for possible ways of achieving gene regulation in experimental research.

Likelihood-based Dynamic Factor Analysis for Measurement and Forecasting

NARCIS (Netherlands)

Jungbacker, B.M.J.P.; Koopman, S.J.

2015-01-01

We present new results for the likelihood-based analysis of the dynamic factor model. The latent factors are modelled by linear dynamic stochastic processes. The idiosyncratic disturbance series are specified as autoregressive processes with mutually correlated innovations. The new results lead to

Reconceptualizing Social Influence in Counseling: The Elaboration Likelihood Model.

Science.gov (United States)

McNeill, Brian W.; Stoltenberg, Cal D.

1989-01-01

Presents Elaboration Likelihood Model (ELM) of persuasion (a reconceptualization of the social influence process) as alternative model of attitude change. Contends ELM unifies conflicting social psychology results and can potentially account for inconsistent research findings in counseling psychology. Provides guidelines on integrating…

El culto de Maximón en Guatemala

OpenAIRE

Pédron‑Colombani, Sylvie

2009-01-01

Este artículo se enfoca en la figura de Maximón, deidad sincrética de Guatemala, en un contexto de desplazamiento de la religión católica popular por parte de las iglesias protestantes. Esta divinidad híbrida a la cual se agregan santos católicos como Judas Iscariote o el dios maya Mam, permite la apropiación de Maximón por segmentos diferenciados de la población (tanto indígena como mestiza). Permite igualmente ser símbolo de protestas sociales enmascaradas cuando se asocia Maximón con figur...

Physician Bayesian updating from personal beliefs about the base rate and likelihood ratio.

Science.gov (United States)

Rottman, Benjamin Margolin

2017-02-01

Whether humans can accurately make decisions in line with Bayes' rule has been one of the most important yet contentious topics in cognitive psychology. Though a number of paradigms have been used for studying Bayesian updating, rarely have subjects been allowed to use their own preexisting beliefs about the prior and the likelihood. A study is reported in which physicians judged the posttest probability of a diagnosis for a patient vignette after receiving a test result, and the physicians' posttest judgments were compared to the normative posttest calculated from their own beliefs in the sensitivity and false positive rate of the test (likelihood ratio) and prior probability of the diagnosis. On the one hand, the posttest judgments were strongly related to the physicians' beliefs about both the prior probability as well as the likelihood ratio, and the priors were used considerably more strongly than in previous research. On the other hand, both the prior and the likelihoods were still not used quite as much as they should have been, and there was evidence of other nonnormative aspects to the updating, such as updating independent of the likelihood beliefs. By focusing on how physicians use their own prior beliefs for Bayesian updating, this study provides insight into how well experts perform probabilistic inference in settings in which they rely upon their own prior beliefs rather than experimenter-provided cues. It suggests that there is reason to be optimistic about experts' abilities, but that there is still considerable need for improvement.

Powdered alcohol: Awareness and likelihood of use among a sample of college students.

Science.gov (United States)

Vail-Smith, Karen; Chaney, Beth H; Martin, Ryan J; Don Chaney, J

2016-01-01

In March 2015, the Alcohol and Tobacco Tax and Trade Bureau approved the sale of Palcohol, the first powdered alcohol product to be marketed and sold in the U.S. Powdered alcohol is freeze-dried, and one individual-serving size packet added to 6 ounces of liquid is equivalent to a standard drink. This study assessed awareness of powered alcohol and likelihood to use and/or misuse powdered alcohol among college students. Surveys were administered to a convenience sample of 1,841 undergraduate students. Only 16.4% of respondents had heard of powdered alcohol. After being provided a brief description of powdered alcohol, 23% indicated that they would use the product if available, and of those, 62.1% also indicated likelihood of misusing the product (eg, snorting it, mixing it with alcohol). Caucasian students (OR = 1.5) and hazardous drinkers (based on AUDIT-C scores; OR = 4.7) were significantly more likely to indicate likelihood of use. Hazardous drinkers were also six times more likely to indicate likelihood to misuse the product. These findings can inform upstream prevention efforts in states debating bans on powdered alcohol. In states where powdered alcohol will soon be available, alcohol education initiatives should be updated to include information on the potential risks of use and be targeted to those populations most likely to misuse. This is the first peer-reviewed study to assess the awareness of and likelihood to use and/or misuse powdered alcohol, a potentially emerging form of alcohol. © American Academy of Addiction Psychiatry.

Practical Statistics for LHC Physicists: Descriptive Statistics, Probability and Likelihood (1/3)

CERN Multimedia

CERN. Geneva

2015-01-01

These lectures cover those principles and practices of statistics that are most relevant for work at the LHC. The first lecture discusses the basic ideas of descriptive statistics, probability and likelihood. The second lecture covers the key ideas in the frequentist approach, including confidence limits, profile likelihoods, p-values, and hypothesis testing. The third lecture covers inference in the Bayesian approach. Throughout, real-world examples will be used to illustrate the practical application of the ideas. No previous knowledge is assumed.

THESEUS: maximum likelihood superpositioning and analysis of macromolecular structures.

Science.gov (United States)

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.

Teleportation protocol with non-ideal conditional local operations

Energy Technology Data Exchange (ETDEWEB)

Di Franco, C., E-mail: cdifranco@caesar.ucc.i [Department of Physics, University College Cork, Cork (Ireland); Ballester, D. [School of Mathematics and Physics, Queen' s University, Belfast BT7 1NN (United Kingdom)

2010-07-12

We analyze teleportation protocol when some of receiver's conditional operations are more reliable than others and a non-maximally entangled channel is shared by the two parts. We show that the average fidelity of teleportation can be maximized by choosing properly the basis in which the sender performs her two-qubit measurement.

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.

Statistical analysis of COMPTEL maximum likelihood-ratio distributions: evidence for a signal from previously undetected AGN

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

Power maximization method for land-transportable fully passive lead–bismuth cooled small modular reactor systems

Energy Technology Data Exchange (ETDEWEB)

Cho, Jaehyun, E-mail: chojh@kaeri.re.kr [Korea Atomic Energy Research Institute, 1405 Daedeok-daero, Yuseong-gu, Daejeon 305-353 (Korea, Republic of); Shin, Yong-Hoon; Hwang, Il Soon [Seoul National University, Sillim-dong, Gwanak-gu, Seoul 151-742 (Korea, Republic of)

2015-08-15

Highlights: • The power maximization method for LBE natural circulation cooled SMRs was developed. • The two powers in view of neutronics and thermal-hydraulics were considered. • The limitations for designing of LBE natural circulation cooled SMRs were summarized. • The necessary conditions for safety shutdown in accidents were developed. • The maximized power in the case study is 206 MW thermal. - Abstract: Although current pressurized water reactors (PWRs) have significantly contributed to global energy supply, PWR technology has not been considered a trustworthy energy solution owing to its problems of spent nuclear fuels (SNFs), nuclear safety, and nuclear economy. In order to overcome these problems, a lead–bismuth eutectic (LBE) fully passive cooling small modular reactor (SMR) system is suggested. This technology can not only provide the solution for the problems of SNFs through the transmutation feature of the LBE coolant, but also strengthen safety and economy through the concept of natural circulation cooling SMRs. It is necessary to maximize the advantages, namely safety and economy, of this type of nuclear power plants for broader applications in the future. Accordingly, the objective of this study is to maximize the reactor core power while satisfying the limitations of shipping size, materials endurance, and criticality of a long-burning core as well as safety under beyond design basis events. To achieve these objectives, the design limitations of natural circulating LBE-cooling SMRs are derived. Then, the power maximization method is developed based on obtaining the design limitations. The results of this study are expected to contribute to the effectiveness of the reactor design stage by providing insights to designers, as well as by formulating methods for the power maximization of other types of SMRs.

Maximizing Lifetime of Wireless Sensor Networks with Mobile Sink Nodes

Directory of Open Access Journals (Sweden)

Yourong Chen

2014-01-01

Full Text Available In order to maximize network lifetime and balance energy consumption when sink nodes can move, maximizing lifetime of wireless sensor networks with mobile sink nodes (MLMS is researched. The movement path selection method of sink nodes is proposed. Modified subtractive clustering method, k-means method, and nearest neighbor interpolation method are used to obtain the movement paths. The lifetime optimization model is established under flow constraint, energy consumption constraint, link transmission constraint, and other constraints. The model is solved from the perspective of static and mobile data gathering of sink nodes. Subgradient method is used to solve the lifetime optimization model when one sink node stays at one anchor location. Geometric method is used to evaluate the amount of gathering data when sink nodes are moving. Finally, all sensor nodes transmit data according to the optimal data transmission scheme. Sink nodes gather the data along the shortest movement paths. Simulation results show that MLMS can prolong network lifetime, balance node energy consumption, and reduce data gathering latency under appropriate parameters. Under certain conditions, it outperforms Ratio_w, TPGF, RCC, and GRND.

Quantitative comparison of OSEM and penalized likelihood image reconstruction using relative difference penalties for clinical PET

International Nuclear Information System (INIS)

Ahn, Sangtae; Asma, Evren; Cheng, Lishui; Manjeshwar, Ravindra M; Ross, Steven G; Miao, Jun; Jin, Xiao; Wollenweber, Scott D

2015-01-01

Ordered subset expectation maximization (OSEM) is the most widely used algorithm for clinical PET image reconstruction. OSEM is usually stopped early and post-filtered to control image noise and does not necessarily achieve optimal quantitation accuracy. As an alternative to OSEM, we have recently implemented a penalized likelihood (PL) image reconstruction algorithm for clinical PET using the relative difference penalty with the aim of improving quantitation accuracy without compromising visual image quality. Preliminary clinical studies have demonstrated visual image quality including lesion conspicuity in images reconstructed by the PL algorithm is better than or at least as good as that in OSEM images. In this paper we evaluate lesion quantitation accuracy of the PL algorithm with the relative difference penalty compared to OSEM by using various data sets including phantom data acquired with an anthropomorphic torso phantom, an extended oval phantom and the NEMA image quality phantom; clinical data; and hybrid clinical data generated by adding simulated lesion data to clinical data. We focus on mean standardized uptake values and compare them for PL and OSEM using both time-of-flight (TOF) and non-TOF data. The results demonstrate improvements of PL in lesion quantitation accuracy compared to OSEM with a particular improvement in cold background regions such as lungs. (paper)

Composite likelihood and two-stage estimation in family studies

DEFF Research Database (Denmark)

Andersen, Elisabeth Anne Wreford

2004-01-01

In this paper register based family studies provide the motivation for linking a two-stage estimation procedure in copula models for multivariate failure time data with a composite likelihood approach. The asymptotic properties of the estimators in both parametric and semi-parametric models are d...

Robust Gaussian Process Regression with a Student-t Likelihood

NARCIS (Netherlands)

Jylänki, P.P.; Vanhatalo, J.; Vehtari, A.

2011-01-01

This paper considers the robust and efficient implementation of Gaussian process regression with a Student-t observation model, which has a non-log-concave likelihood. The challenge with the Student-t model is the analytically intractable inference which is why several approximative methods have

Autistic disorders and schizophrenia: related or remote? An anatomical likelihood estimation.

Directory of Open Access Journals (Sweden)

Charlton Cheung

Full Text Available Shared genetic and environmental risk factors have been identified for autistic spectrum disorders (ASD and schizophrenia. Social interaction, communication, emotion processing, sensorimotor gating and executive function are disrupted in both, stimulating debate about whether these are related conditions. Brain imaging studies constitute an informative and expanding resource to determine whether brain structural phenotype of these disorders is distinct or overlapping. We aimed to synthesize existing datasets characterizing ASD and schizophrenia within a common framework, to quantify their structural similarities. In a novel modification of Anatomical Likelihood Estimation (ALE, 313 foci were extracted from 25 voxel-based studies comprising 660 participants (308 ASD, 352 first-episode schizophrenia and 801 controls. The results revealed that, compared to controls, lower grey matter volumes within limbic-striato-thalamic circuitry were common to ASD and schizophrenia. Unique features of each disorder included lower grey matter volume in amygdala, caudate, frontal and medial gyrus for schizophrenia and putamen for autism. Thus, in terms of brain volumetrics, ASD and schizophrenia have a clear degree of overlap that may reflect shared etiological mechanisms. However, the distinctive neuroanatomy also mapped in each condition raises the question about how this is arrived in the context of common etiological pressures.

Trainability of muscular activity level during maximal voluntary co-contraction: comparison between bodybuilders and nonathletes.

Directory of Open Access Journals (Sweden)

Sumiaki Maeo

Full Text Available Antagonistic muscle pairs cannot be fully activated simultaneously, even with maximal effort, under conditions of voluntary co-contraction, and their muscular activity levels are always below those during agonist contraction with maximal voluntary effort (MVE. Whether the muscular activity level during the task has trainability remains unclear. The present study examined this issue by comparing the muscular activity level during maximal voluntary co-contraction for highly experienced bodybuilders, who frequently perform voluntary co-contraction in their training programs, with that for untrained individuals (nonathletes. The electromyograms (EMGs of biceps brachii and triceps brachii muscles during maximal voluntary co-contraction of elbow flexors and extensors were recorded in 11 male bodybuilders and 10 nonathletes, and normalized to the values obtained during the MVE of agonist contraction for each of the corresponding muscles (% EMGMVE. The involuntary coactivation level in antagonist muscle during the MVE of agonist contraction was also calculated. In both muscles, % EMGMVE values during the co-contraction task for bodybuilders were significantly higher (P<0.01 than those for nonathletes (biceps brachii: 66±14% in bodybuilders vs. 46±13% in nonathletes, triceps brachii: 74±16% vs. 57±9%. There was a significant positive correlation between a length of bodybuilding experience and muscular activity level during the co-contraction task (r = 0.653, P = 0.03. Involuntary antagonist coactivation level during MVE of agonist contraction was not different between the two groups. The current result indicates that long-term participation in voluntary co-contraction training progressively enhances muscular activity during maximal voluntary co-contraction.

Trainability of Muscular Activity Level during Maximal Voluntary Co-Contraction: Comparison between Bodybuilders and Nonathletes

Science.gov (United States)

Maeo, Sumiaki; Takahashi, Takumi; Takai, Yohei; Kanehisa, Hiroaki

2013-01-01

Antagonistic muscle pairs cannot be fully activated simultaneously, even with maximal effort, under conditions of voluntary co-contraction, and their muscular activity levels are always below those during agonist contraction with maximal voluntary effort (MVE). Whether the muscular activity level during the task has trainability remains unclear. The present study examined this issue by comparing the muscular activity level during maximal voluntary co-contraction for highly experienced bodybuilders, who frequently perform voluntary co-contraction in their training programs, with that for untrained individuals (nonathletes). The electromyograms (EMGs) of biceps brachii and triceps brachii muscles during maximal voluntary co-contraction of elbow flexors and extensors were recorded in 11 male bodybuilders and 10 nonathletes, and normalized to the values obtained during the MVE of agonist contraction for each of the corresponding muscles (% EMGMVE). The involuntary coactivation level in antagonist muscle during the MVE of agonist contraction was also calculated. In both muscles, % EMGMVE values during the co-contraction task for bodybuilders were significantly higher (Pbodybuilders vs. 46±13% in nonathletes, triceps brachii: 74±16% vs. 57±9%). There was a significant positive correlation between a length of bodybuilding experience and muscular activity level during the co-contraction task (r = 0.653, P = 0.03). Involuntary antagonist coactivation level during MVE of agonist contraction was not different between the two groups. The current result indicates that long-term participation in voluntary co-contraction training progressively enhances muscular activity during maximal voluntary co-contraction. PMID:24260233

Differences and implications in biogeochemistry from maximizing entropy production locally versus globally

Directory of Open Access Journals (Sweden)

J. J. Vallino

2011-06-01

Full Text Available In this manuscript we investigate the use of the maximum entropy production (MEP principle for modeling biogeochemical processes that are catalyzed by living systems. Because of novelties introduced by the MEP approach, many questions need to be answered and techniques developed in the application of MEP to describe biological systems that are responsible for energy and mass transformations on a planetary scale. In previous work we introduce the importance of integrating entropy production over time to distinguish abiotic from biotic processes under transient conditions. Here we investigate the ramifications of modeling biological systems involving one or more spatial dimensions. When modeling systems over space, entropy production can be maximized either locally at each point in space asynchronously or globally over the system domain synchronously. We use a simple two-box model inspired by two-layer ocean models to illustrate the differences in local versus global entropy maximization. Synthesis and oxidation of biological structure is modeled using two autocatalytic reactions that account for changes in community kinetics using a single parameter each. Our results show that entropy production can be increased if maximized over the system domain rather than locally, which has important implications regarding how biological systems organize and supports the hypothesis for multiple levels of selection and cooperation in biology for the dissipation of free energy.

Assessment of the Maximal Split-Half Coefficient to Estimate Reliability

Science.gov (United States)

Thompson, Barry L.; Green, Samuel B.; Yang, Yanyun

2010-01-01

The maximal split-half coefficient is computed by calculating all possible split-half reliability estimates for a scale and then choosing the maximal value as the reliability estimate. Osburn compared the maximal split-half coefficient with 10 other internal consistency estimates of reliability and concluded that it yielded the most consistently…

Learning curves for mutual information maximization

International Nuclear Information System (INIS)

Urbanczik, R.

2003-01-01

An unsupervised learning procedure based on maximizing the mutual information between the outputs of two networks receiving different but statistically dependent inputs is analyzed [S. Becker and G. Hinton, Nature (London) 355, 161 (1992)]. For a generic data model, I show that in the large sample limit the structure in the data is recognized by mutual information maximization. For a more restricted model, where the networks are similar to perceptrons, I calculate the learning curves for zero-temperature Gibbs learning. These show that convergence can be rather slow, and a way of regularizing the procedure is considered

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....

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

Breakdown of maximality conjecture in continuous phase transitions

International Nuclear Information System (INIS)

Mukamel, D.; Jaric, M.V.

1983-04-01

A Landau-Ginzburg-Wilson model associated with a single irreducible representation which exhibits an ordered phase whose symmetry group is not a maximal isotropy subgroup of the symmetry group of the disordered phase is constructed. This example disproves the maximality conjecture suggested in numerous previous studies. Below the (continuous) transition, the order parameter points along a direction which varies with the temperature and with the other parameters which define the model. An extension of the maximality conjecture to reducible representations was postulated in the context of Higgs symmetry breaking mechanism. Our model can also be extended to provide a counter example in these cases. (author)

Maximizers versus satisficers: Decision-making styles, competence, and outcomes

OpenAIRE

Andrew M. Parker; Wändi Bruine de Bruin; Baruch Fischhoff

2007-01-01

Our previous research suggests that people reporting a stronger desire to maximize obtain worse life outcomes (Bruine de Bruin et al., 2007). Here, we examine whether this finding may be explained by the decision-making styles of self-reported maximizers. Expanding on Schwartz et al.\\ (2002), we find that self-reported maximizers are more likely to show problematic decision-making styles, as evidenced by self-reports of less behavioral coping, greater dependence on others when making decision...

Neutrino mass textures with maximal CP violation

International Nuclear Information System (INIS)

Aizawa, Ichiro; Kitabayashi, Teruyuki; Yasue, Masaki

2005-01-01

We show three types of neutrino mass textures, which give maximal CP violation as well as maximal atmospheric neutrino mixing. These textures are described by six real mass parameters: one specified by two complex flavor neutrino masses and two constrained ones and the others specified by three complex flavor neutrino masses. In each texture, we calculate mixing angles and masses, which are consistent with observed data, as well as Majorana CP phases

Likelihood analysis of supersymmetric SU(5) GUTs

Energy Technology Data Exchange (ETDEWEB)

Bagnaschi, E.; Weiglein, G. [DESY, Hamburg (Germany); Costa, J.C.; Buchmueller, O.; Citron, M.; Richards, A.; De Vries, K.J. [Imperial College, High Energy Physics Group, Blackett Laboratory, London (United Kingdom); Sakurai, K. [University of Durham, Science Laboratories, Department of Physics, Institute for Particle Physics Phenomenology, Durham (United Kingdom); University of Warsaw, Faculty of Physics, Institute of Theoretical Physics, Warsaw (Poland); Borsato, M.; Chobanova, V.; Lucio, M.; Martinez Santos, D. [Universidade de Santiago de Compostela, Santiago de Compostela (Spain); Cavanaugh, R. [Fermi National Accelerator Laboratory, Batavia, IL (United States); University of Illinois at Chicago, Physics Department, Chicago, IL (United States); Roeck, A. de [CERN, Experimental Physics Department, Geneva (Switzerland); Antwerp University, Wilrijk (Belgium); Dolan, M.J. [University of Melbourne, ARC Centre of Excellence for Particle Physics at the Terascale, School of Physics, Parkville (Australia); Ellis, J.R. [King' s College London, Theoretical Particle Physics and Cosmology Group, Department of Physics, London (United Kingdom); Theoretical Physics Department, CERN, Geneva 23 (Switzerland); Flaecher, H. [University of Bristol, H.H. Wills Physics Laboratory, Bristol (United Kingdom); Heinemeyer, S. [Campus of International Excellence UAM+CSIC, Cantoblanco, Madrid (Spain); Instituto de Fisica Teorica UAM-CSIC, Madrid (Spain); Instituto de Fisica de Cantabria (CSIC-UC), Santander (Spain); Isidori, G. [Universitaet Zuerich, Physik-Institut, Zurich (Switzerland); Olive, K.A. [University of Minnesota, William I. Fine Theoretical Physics Institute, School of Physics and Astronomy, Minneapolis, MN (United States)

2017-02-15

We perform a likelihood analysis of the constraints from accelerator experiments and astrophysical observations on supersymmetric (SUSY) models with SU(5) boundary conditions on soft SUSY-breaking parameters at the GUT scale. The parameter space of the models studied has seven parameters: a universal gaugino mass m{sub 1/2}, distinct masses for the scalar partners of matter fermions in five- and ten-dimensional representations of SU(5), m{sub 5} and m{sub 10}, and for the 5 and anti 5 Higgs representations m{sub H{sub u}} and m{sub H{sub d}}, a universal trilinear soft SUSY-breaking parameter A{sub 0}, and the ratio of Higgs vevs tan β. In addition to previous constraints from direct sparticle searches, low-energy and flavour observables, we incorporate constraints based on preliminary results from 13 TeV LHC searches for jets + E{sub T} events and long-lived particles, as well as the latest PandaX-II and LUX searches for direct Dark Matter detection. In addition to previously identified mechanisms for bringing the supersymmetric relic density into the range allowed by cosmology, we identify a novel u{sub R}/c{sub R} - χ{sup 0}{sub 1} coannihilation mechanism that appears in the supersymmetric SU(5) GUT model and discuss the role of ν{sub τ} coannihilation. We find complementarity between the prospects for direct Dark Matter detection and SUSY searches at the LHC. (orig.)

Likelihood analysis of supersymmetric SU(5) GUTs

Energy Technology Data Exchange (ETDEWEB)

Bagnaschi, E. [DESY, Hamburg (Germany); Costa, J.C. [Imperial College, London (United Kingdom). Blackett Lab.; Sakurai, K. [Durham Univ. (United Kingdom). Inst. for Particle Physics Phenomonology; Warsaw Univ. (Poland). Inst. of Theoretical Physics; Collaboration: MasterCode Collaboration; and others

2016-10-15

We perform a likelihood analysis of the constraints from accelerator experiments and astrophysical observations on supersymmetric (SUSY) models with SU(5) boundary conditions on soft SUSY-breaking parameters at the GUT scale. The parameter space of the models studied has 7 parameters: a universal gaugino mass m{sub 1/2}, distinct masses for the scalar partners of matter fermions in five- and ten-dimensional representations of SU(5), m{sub 5} and m{sub 10}, and for the 5 and anti 5 Higgs representations m{sub H{sub u}} and m{sub H{sub d}}, a universal trilinear soft SUSY-breaking parameter A{sub 0}, and the ratio of Higgs vevs tan β. In addition to previous constraints from direct sparticle searches, low-energy and avour observables, we incorporate constraints based on preliminary results from 13 TeV LHC searches for jets+E{sub T} events and long-lived particles, as well as the latest PandaX-II and LUX searches for direct Dark Matter detection. In addition to previously-identified mechanisms for bringing the supersymmetric relic density into the range allowed by cosmology, we identify a novel u{sub R}/c{sub R}-χ{sup 0}{sub 1} coannihilation mechanism that appears in the supersymmetric SU(5) GUT model and discuss the role of ν{sub T} coannihilation. We find complementarity between the prospects for direct Dark Matter detection and SUSY searches at the LHC.

The Impact of Firefighter Personal Protective Equipment and Treadmill Protocol on Maximal Oxygen Uptake

Science.gov (United States)

Lee, Joo-Young; Bakri, Ilham; Kim, Jung-Hyun; Son, Su-Young; Tochihara, Yutaka

2015-01-01

This study investigated the effects of firefighter personal protective equipment (PPE) on the determination of maximal oxygen uptake (VO2max) while using two different treadmill protocols: a progressive incline protocol (PIP) and a progressive speed protocol (PSP), with three clothing conditions (Light-light clothing; Boots-PPE with rubber boots; Shoes-PPE with running shoes). Bruce protocol with Light was performed for a reference test. Results showed there was no difference in VO2max between Bruce Light, PIP Light, and PSP Light. However, VO2max was reduced in Boots and Shoes with shortened maximal performance time (7 and 6 min reduced for PIP Boots and Shoes, respectively; 11 and 9 min reduced for PSP Boots and Shoes, respectively), whereas the increasing rate of VO2 in Boots and Shoes during submaximal exercise was greater compared with Light. Wearing firefighter boots compared with wearing running shoes also significantly affected submaximal VO2 but not VO2max. These results suggest that firefighters’ maximal performance determined from a typical VO2max test without wearing PPE may overestimate the actual performance capability of firefighters wearing PPE. PMID:23668854

Comparison of changes in the mobility of the pelvic floor muscle on during the abdominal drawing-in maneuver, maximal expiration, and pelvic floor muscle maximal contraction

OpenAIRE

Jung, Halim; Jung, Sangwoo; Joo, Sunghee; Song, Changho

2016-01-01

[Purpose] The purpose of this study was to compare changes in the mobility of the pelvic floor muscle during the abdominal drawing-in maneuver, maximal expiration, and pelvic floor muscle maximal contraction. [Subjects] Thirty healthy adults participated in this study (15 men and 15 women). [Methods] All participants performed a bridge exercise and abdominal curl-up during the abdominal drawing-in maneuver, maximal expiration, and pelvic floor muscle maximal contraction. Pelvic floor mobility...

Quantifying uncertainty, variability and likelihood for ordinary differential equation models

LENUS (Irish Health Repository)

Weisse, Andrea Y

2010-10-28

Abstract Background In many applications, ordinary differential equation (ODE) models are subject to uncertainty or variability in initial conditions and parameters. Both, uncertainty and variability can be quantified in terms of a probability density function on the state and parameter space. Results The partial differential equation that describes the evolution of this probability density function has a form that is particularly amenable to application of the well-known method of characteristics. The value of the density at some point in time is directly accessible by the solution of the original ODE extended by a single extra dimension (for the value of the density). This leads to simple methods for studying uncertainty, variability and likelihood, with significant advantages over more traditional Monte Carlo and related approaches especially when studying regions with low probability. Conclusions While such approaches based on the method of characteristics are common practice in other disciplines, their advantages for the study of biological systems have so far remained unrecognized. Several examples illustrate performance and accuracy of the approach and its limitations.

Menyoal Elaboration Likelihood Model (ELM dan Teori Retorika

Directory of Open Access Journals (Sweden)

Yudi Perbawaningsih

2012-06-01

Full Text Available Abstract: Persuasion is a communication process to establish or change attitudes, which can be understood through theory of Rhetoric and theory of Elaboration Likelihood Model (ELM. This study elaborates these theories in a Public Lecture series which to persuade the students in choosing their concentration of study. The result shows that in term of persuasion effectiveness it is not quite relevant to separate the message and its source. The quality of source is determined by the quality of the message, and vice versa. Separating the two routes of the persuasion process as described in the ELM theory would not be relevant. Abstrak: Persuasi adalah proses komunikasi untuk membentuk atau mengubah sikap, yang dapat dipahami dengan teori Retorika dan teori Elaboration Likelihood Model (ELM. Penelitian ini mengelaborasi teori tersebut dalam Kuliah Umum sebagai sarana mempersuasi mahasiswa untuk memilih konsentrasi studi studi yang didasarkan pada proses pengolahan informasi. Menggunakan metode survey, didapatkan hasil yaitu tidaklah cukup relevan memisahkan pesan dan narasumber dalam melihat efektivitas persuasi. Keduanya menyatu yang berarti bahwa kualitas narasumber ditentukan oleh kualitas pesan yang disampaikannya, dan sebaliknya. Memisahkan proses persuasi dalam dua lajur seperti yang dijelaskan dalam ELM teori menjadi tidak relevan.

Myocardial functional responses do not contribute to maximal exercise performance in the heat.

Science.gov (United States)

Smith, Denise L; DeBlois, Jacob P; Wharton, Margaret; Rowland, Thomas

2015-01-01

Both the extent and means by which maximal oxygen uptake ([Formula: see text]) is depressed by elevated ambient temperature are uncertain. Particularly, information is currently unavailable regarding the possible influence of alterations in myocardial function on [Formula: see text] and performance during exercise in the heat. This study investigated the effects of environmental heat on [Formula: see text], peak work capacity, and myocardial function during a standard, progressive cycle test to exhaustion. Twelve euhydrated men (aged 20.7 ± 1.7 years) performed a maximal cycle test in an environmental chamber in both heat stress [35°C, 30% relative humidity (RH)] and temperate (20°C, 30% RH) conditions with measurement of standard gas exchange variables, core temperature, and echocardiographic measures of cardiac function. A small but statistically significant reduction of peak work capacity was observed in the heat stress versus temperate conditions (253 ± 30 and 259 ± 30 W, respectively, p = 0.02). Mean [Formula: see text] was not statistically different in the two conditions (p = 0.16) but values were 3.4% lower in the heat, and 9 of 12 participants demonstrated lower values in the heat stress trial. No differences in responses of heart rate, cardiac output, stroke volume, core temperature, hydration status, or myocardial systolic or diastolic function were observed between the two conditions, but perceived body temperature was higher in the heat. The small, negative impact of heat on exercise performance and [Formula: see text] could not be explained by disturbances in myocardial functional responses to exercise in young adult males.

Effects of Hemopure on maximal oxygen uptake and endurance performance in healthy humans.

Science.gov (United States)

Ashenden, M J; Schumacher, Y O; Sharpe, K; Varlet-Marie, E; Audran, M

2007-05-01

Haemoglobin-based oxygen carriers (HBOCs) such as Hemopure are touted as a tenable substitute for red blood cells and therefore potential doping agents, although the mechanisms of oxygen transport of HBOCs are incompletely understood. We investigated whether infusion of Hemopure increased maximal oxygen uptake (V.O 2max) and endurance performance in healthy subjects. Twelve male subjects performed two 4-minute submaximal exercise bouts equivalent to 60 % and 75 % of V.O (2max) on a cycle ergometer, followed by a ramped incremental protocol to elicit V.O (2max). A crossover design tested the effect of infusing either 30 g (6 subjects) or 45 g (6 subjects) of Hemopure versus a placebo. Under our study conditions, Hemopure did not increase V.O (2max) nor endurance performance. However, the infusion of Hemopure caused a decrease in heart rate of approximately 10 bpm (p=0.009) and an average increase in mean ( approximately 7 mmHg) and diastolic blood pressure ( approximately 8 mmHg) (p=0.046) at submaximal and maximal exercise intensities. Infusion of Hemopure did not bestow the same physiological advantages generally associated with infusion of red blood cells. It is conceivable that under exercise conditions, the hypertensive effects of Hemopure counter the performance-enhancing effect of improved blood oxygen carrying capacity.

Quasideterministic generation of maximally entangled states of two mesoscopic atomic ensembles by adiabatic quantum feedback

International Nuclear Information System (INIS)

Di Lisi, Antonio; De Siena, Silvio; Illuminati, Fabrizio; Vitali, David

2005-01-01

We introduce an efficient, quasideterministic scheme to generate maximally entangled states of two atomic ensembles. The scheme is based on quantum nondemolition measurements of total atomic populations and on adiabatic quantum feedback conditioned by the measurements outputs. The high efficiency of the scheme is tested and confirmed numerically for ideal photodetection as well as in the presence of losses

Maximally-localized position, Euclidean path-integral, and thermodynamics in GUP quantum mechanics

Science.gov (United States)

Bernardo, Reginald Christian S.; Esguerra, Jose Perico H.

2018-04-01

In dealing with quantum mechanics at very high energies, it is essential to adapt to a quasiposition representation using the maximally-localized states because of the generalized uncertainty principle. In this paper, we look at maximally-localized states as eigenstates of the operator ξ = X + iβP that we refer to as the maximally-localized position. We calculate the overlap between maximally-localized states and show that the identity operator can be expressed in terms of the maximally-localized states. Furthermore, we show that the maximally-localized position is diagonal in momentum-space and that the maximally-localized position and its adjoint satisfy commutation and anti-commutation relations reminiscent of the harmonic oscillator commutation and anti-commutation relations. As application, we use the maximally-localized position in developing the Euclidean path-integral and introduce the compact form of the propagator for maximal localization. The free particle momentum-space propagator and the propagator for maximal localization are analytically evaluated up to quadratic-order in β. Finally, we obtain a path-integral expression for the partition function of a thermodynamic system using the maximally-localized states. The partition function of a gas of noninteracting particles is evaluated. At temperatures exceeding the Planck energy, we obtain the gas' maximum internal energy N / 2 β and recover the zero heat capacity of an ideal gas.

Gaussian likelihood inference on data from trans-Gaussian random fields with Matérn covariance function

KAUST Repository

Yan, Yuan; Genton, Marc G.

2017-01-01

Gaussian likelihood inference has been studied and used extensively in both statistical theory and applications due to its simplicity. However, in practice, the assumption of Gaussianity is rarely met in the analysis of spatial data. In this paper, we study the effect of non-Gaussianity on Gaussian likelihood inference for the parameters of the Matérn covariance model. By using Monte Carlo simulations, we generate spatial data from a Tukey g-and-h random field, a flexible trans-Gaussian random field, with the Matérn covariance function, where g controls skewness and h controls tail heaviness. We use maximum likelihood based on the multivariate Gaussian distribution to estimate the parameters of the Matérn covariance function. We illustrate the effects of non-Gaussianity of the data on the estimated covariance function by means of functional boxplots. Thanks to our tailored simulation design, a comparison of the maximum likelihood estimator under both the increasing and fixed domain asymptotics for spatial data is performed. We find that the maximum likelihood estimator based on Gaussian likelihood is overall satisfying and preferable than the non-distribution-based weighted least squares estimator for data from the Tukey g-and-h random field. We also present the result for Gaussian kriging based on Matérn covariance estimates with data from the Tukey g-and-h random field and observe an overall satisfactory performance.

Gaussian likelihood inference on data from trans-Gaussian random fields with Matérn covariance function

KAUST Repository

Yan, Yuan

2017-07-13

Gaussian likelihood inference has been studied and used extensively in both statistical theory and applications due to its simplicity. However, in practice, the assumption of Gaussianity is rarely met in the analysis of spatial data. In this paper, we study the effect of non-Gaussianity on Gaussian likelihood inference for the parameters of the Matérn covariance model. By using Monte Carlo simulations, we generate spatial data from a Tukey g-and-h random field, a flexible trans-Gaussian random field, with the Matérn covariance function, where g controls skewness and h controls tail heaviness. We use maximum likelihood based on the multivariate Gaussian distribution to estimate the parameters of the Matérn covariance function. We illustrate the effects of non-Gaussianity of the data on the estimated covariance function by means of functional boxplots. Thanks to our tailored simulation design, a comparison of the maximum likelihood estimator under both the increasing and fixed domain asymptotics for spatial data is performed. We find that the maximum likelihood estimator based on Gaussian likelihood is overall satisfying and preferable than the non-distribution-based weighted least squares estimator for data from the Tukey g-and-h random field. We also present the result for Gaussian kriging based on Matérn covariance estimates with data from the Tukey g-and-h random field and observe an overall satisfactory performance.

Why firms should not always maximize profits

OpenAIRE

Kolstad, Ivar

2006-01-01

Though corporate social responsibility (CSR) is on the agenda of most major corporations, corporate executives still largely support the view that corporations should maximize the returns to their owners. There are two lines of defence for this position. One is the Friedmanian view that maximizing owner returns is the corporate social responsibility of corporations. The other is a position voiced by many executives, that CSR and profits go together. This paper argues that the first position i...

L.U.St: a tool for approximated maximum likelihood supertree reconstruction.

Science.gov (United States)

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.

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

Analyzing multivariate survival data using composite likelihood and flexible parametric modeling of the hazard functions

DEFF Research Database (Denmark)

Nielsen, Jan; Parner, Erik

2010-01-01

In this paper, we model multivariate time-to-event data by composite likelihood of pairwise frailty likelihoods and marginal hazards using natural cubic splines. Both right- and interval-censored data are considered. The suggested approach is applied on two types of family studies using the gamma...

Maximizing band gaps in plate structures

DEFF Research Database (Denmark)

Halkjær, Søren; Sigmund, Ole; Jensen, Jakob Søndergaard

2006-01-01

periodic plate using Bloch theory, which conveniently reduces the maximization problem to that of a single base cell. Secondly, we construct a finite periodic plate using a number of the optimized base cells in a postprocessed version. The dynamic properties of the finite plate are investigated......Band gaps, i.e., frequency ranges in which waves cannot propagate, can be found in elastic structures for which there is a certain periodic modulation of the material properties or structure. In this paper, we maximize the band gap size for bending waves in a Mindlin plate. We analyze an infinite...... theoretically and experimentally and the issue of finite size effects is addressed....

Finding Maximal Pairs with Bounded Gap

DEFF Research Database (Denmark)

Brodal, Gerth Stølting; Lyngsø, Rune B.; Pedersen, Christian N. S.

1999-01-01

. In this paper we present methods for finding all maximal pairs under various constraints on the gap. In a string of length n we can find all maximal pairs with gap in an upper and lower bounded interval in time O(n log n+z) where z is the number of reported pairs. If the upper bound is removed the time reduces...... to O(n+z). Since a tandem repeat is a pair where the gap is zero, our methods can be seen as a generalization of finding tandem repeats. The running time of our methods equals the running time of well known methods for finding tandem repeats....

Likelihood inference of non-constant diversification rates with incomplete taxon sampling.

Science.gov (United States)

Höhna, Sebastian

2014-01-01

Large-scale phylogenies provide a valuable source to study background diversification rates and investigate if the rates have changed over time. Unfortunately most large-scale, dated phylogenies are sparsely sampled (fewer than 5% of the described species) and taxon sampling is not uniform. Instead, taxa are frequently sampled to obtain at least one representative per subgroup (e.g. family) and thus to maximize diversity (diversified sampling). So far, such complications have been ignored, potentially biasing the conclusions that have been reached. In this study I derive the likelihood of a birth-death process with non-constant (time-dependent) diversification rates and diversified taxon sampling. Using simulations I test if the true parameters and the sampling method can be recovered when the trees are small or medium sized (fewer than 200 taxa). The results show that the diversification rates can be inferred and the estimates are unbiased for large trees but are biased for small trees (fewer than 50 taxa). Furthermore, model selection by means of Akaike's Information Criterion favors the true model if the true rates differ sufficiently from alternative models (e.g. the birth-death model is recovered if the extinction rate is large and compared to a pure-birth model). Finally, I applied six different diversification rate models--ranging from a constant-rate pure birth process to a decreasing speciation rate birth-death process but excluding any rate shift models--on three large-scale empirical phylogenies (ants, mammals and snakes with respectively 149, 164 and 41 sampled species). All three phylogenies were constructed by diversified taxon sampling, as stated by the authors. However only the snake phylogeny supported diversified taxon sampling. Moreover, a parametric bootstrap test revealed that none of the tested models provided a good fit to the observed data. The model assumptions, such as homogeneous rates across species or no rate shifts, appear to be

The key kinematic determinants of undulatory underwater swimming at maximal velocity.

Science.gov (United States)

Connaboy, Chris; Naemi, Roozbeh; Brown, Susan; Psycharakis, Stelios; McCabe, Carla; Coleman, Simon; Sanders, Ross

2016-01-01

The optimisation of undulatory underwater swimming is highly important in competitive swimming performance. Nineteen kinematic variables were identified from previous research undertaken to assess undulatory underwater swimming performance. The purpose of the present study was to determine which kinematic variables were key to the production of maximal undulatory underwater swimming velocity. Kinematic data at maximal undulatory underwater swimming velocity were collected from 17 skilled swimmers. A series of separate backward-elimination analysis of covariance models was produced with cycle frequency and cycle length as dependent variables (DVs) and participant as a fixed factor, as including cycle frequency and cycle length would explain 100% of the maximal swimming velocity variance. The covariates identified in the cycle-frequency and cycle-length models were used to form the saturated model for maximal swimming velocity. The final parsimonious model identified three covariates (maximal knee joint angular velocity, maximal ankle angular velocity and knee range of movement) as determinants of the variance in maximal swimming velocity (adjusted-r2 = 0.929). However, when participant was removed as a fixed factor there was a large reduction in explained variance (adjusted r2 = 0.397) and only maximal knee joint angular velocity continued to contribute significantly, highlighting its importance to the production of maximal swimming velocity. The reduction in explained variance suggests an emphasis on inter-individual differences in undulatory underwater swimming technique and/or anthropometry. Future research should examine the efficacy of other anthropometric, kinematic and coordination variables to better understand the production of maximal swimming velocity and consider the importance of individual undulatory underwater swimming techniques when interpreting the data.

Kinetic theory in maximal-acceleration invariant phase space

International Nuclear Information System (INIS)

Brandt, H.E.

1989-01-01

A vanishing directional derivative of a scalar field along particle trajectories in maximal acceleration invariant phase space is identical in form to the ordinary covariant Vlasov equation in curved spacetime in the presence of both gravitational and nongravitational forces. A natural foundation is thereby provided for a covariant kinetic theory of particles in maximal-acceleration invariant phase space. (orig.)

Descent of line bundles to GIT quotients of flag varieties by maximal torus

OpenAIRE

Kumar, Shrawan

2007-01-01

Let L be a homogeneous ample line bundle on any flag variety G/P and let T be a maximal torus of G. We prove a general necessary and sufficient condition for L to descend as a line bundle on the GIT quotient of G/P by T. We use this result to explicitly determine exactly which L descend to the GIT quotient for any simple complex algebraic group G and any parabolic subgroup P.

MAXIMUM-LIKELIHOOD-ESTIMATION OF THE ENTROPY OF AN ATTRACTOR

NARCIS (Netherlands)

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

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

On Bayesian Testing of Additive Conjoint Measurement Axioms Using Synthetic Likelihood.

Science.gov (United States)

Karabatsos, George

2018-06-01

This article introduces a Bayesian method for testing the axioms of additive conjoint measurement. The method is based on an importance sampling algorithm that performs likelihood-free, approximate Bayesian inference using a synthetic likelihood to overcome the analytical intractability of this testing problem. This new method improves upon previous methods because it provides an omnibus test of the entire hierarchy of cancellation axioms, beyond double cancellation. It does so while accounting for the posterior uncertainty that is inherent in the empirical orderings that are implied by these axioms, together. The new method is illustrated through a test of the cancellation axioms on a classic survey data set, and through the analysis of simulated data.

Narrow band interference cancelation in OFDM: Astructured maximum likelihood approach

KAUST Repository

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

Mobile sensing of point-source fugitive methane emissions using Bayesian inference: the determination of the likelihood function

Science.gov (United States)

Zhou, X.; Albertson, J. D.

2016-12-01

Natural gas is considered as a bridge fuel towards clean energy due to its potential lower greenhouse gas emission comparing with other fossil fuels. Despite numerous efforts, an efficient and cost-effective approach to monitor fugitive methane emissions along the natural gas production-supply chain has not been developed yet. Recently, mobile methane measurement has been introduced which applies a Bayesian approach to probabilistically infer methane emission rates and update estimates recursively when new measurements become available. However, the likelihood function, especially the error term which determines the shape of the estimate uncertainty, is not rigorously defined and evaluated with field data. To address this issue, we performed a series of near-source (using a specialized vehicle mounted with fast response methane analyzers and a GPS unit. Methane concentrations were measured at two different heights along mobile traversals downwind of the sources, and concurrent wind and temperature data are recorded by nearby 3-D sonic anemometers. With known methane release rates, the measurements were used to determine the functional form and the parameterization of the likelihood function in the Bayesian inference scheme under different meteorological conditions.

Longer duration of homelessness is associated with a lower likelihood of non-detectable plasma HIV-1 RNA viral load among people who use illicit drugs in a Canadian setting.

Science.gov (United States)

Loh, Jane; Kennedy, Mary Clare; Wood, Evan; Kerr, Thomas; Marshall, Brandon; Parashar, Surita; Montaner, Julio; Milloy, M-J

2016-11-01

Homelessness is common among people who use drugs (PWUD) and, for those living with HIV/AIDS, an important contributor to sub-optimal HIV treatment outcomes. This study aims to investigate the relationship between the duration of homelessness and the likelihood of plasma HIV-1 RNA viral load (VL) non-detectability among a cohort of HIV-positive PWUD. We used data from the ACCESS study, a long-running prospective cohort study of HIV-positive PWUD linked to comprehensive HIV clinical records including systematic plasma HIV-1 RNA VL monitoring. We estimated the longitudinal relationship between the duration of homelessness and the likelihood of exhibiting a non-detectable VL (i.e., effects modelling. Between May 1996 and June 2014, 922 highly active antiretroviral therapy-exposed participants were recruited and contributed 8188 observations. Of these, 4800 (59%) were characterized by non-detectable VL. Participants reported they were homeless in 910 (11%) interviews (median: six months, interquartile range: 6-12 months). A longer duration of homelessness was associated with lower odds of VL non-detectability (adjusted odds ratio = 0.71 per six-month period of homelessness, 95% confidence interval: 0.60-0.83) after adjustment for age, ancestry, drug use patterns, engagement in addiction treatment, and other potential confounders. Longer durations of episodes of homelessness in this cohort of HIV-positive illicit drug users were associated with a lower likelihood of plasma VL non-detectability. Our findings suggest that interventions that seek to promptly house homeless individuals, such as Housing First approaches, might assist in maximizing the clinical and public health benefits of antiretroviral therapy among people living with HIV/AIDS.

Left ventricle expands maximally preceding end-diastole. Radionuclide ventriculography study

International Nuclear Information System (INIS)

Horinouchi, Osamu

2002-01-01

It has been considered that left ventricle (LV) expands maximally at the end-diastole. However, is it exactly coincident with this point? This study was aimed to determine whether the maximal expansion of LV coincides with the peak of R wave on electrocardiogram. Thirty-three angina pectoris patients with normal LV motion were examined using radionuclide ventriculography. Data were obtained from every 30 ms backward frame from the peak of R wave. All patients showed the time of maximal expansion preceded the peak of R wave. The intervals from the peak of R wave and the onset of P wave to maximal expansion of LV was 105±29 ms and 88±25 ms, respectively. This period corresponds to the timing of maximal excurtion of mitral valve by atrial contraction, and the centripetal motion of LV without losing its volume before end-diastole may be interpreted on account of the movement of mitral valve toward closure. These findings suggest that LV expands maximally between P and R wave after atrial contraction, preceding the peak of R wave thought conventionally as the end-diastole. (author)

Likelihood-based methods for evaluating principal surrogacy in augmented vaccine trials.

Science.gov (United States)

Liu, Wei; Zhang, Bo; Zhang, Hui; Zhang, Zhiwei

2017-04-01

There is growing interest in assessing immune biomarkers, which are quick to measure and potentially predictive of long-term efficacy, as surrogate endpoints in randomized, placebo-controlled vaccine trials. This can be done under a principal stratification approach, with principal strata defined using a subject's potential immune responses to vaccine and placebo (the latter may be assumed to be zero). In this context, principal surrogacy refers to the extent to which vaccine efficacy varies across principal strata. Because a placebo recipient's potential immune response to vaccine is unobserved in a standard vaccine trial, augmented vaccine trials have been proposed to produce the information needed to evaluate principal surrogacy. This article reviews existing methods based on an estimated likelihood and a pseudo-score (PS) and proposes two new methods based on a semiparametric likelihood (SL) and a pseudo-likelihood (PL), for analyzing augmented vaccine trials. Unlike the PS method, the SL method does not require a model for missingness, which can be advantageous when immune response data are missing by happenstance. The SL method is shown to be asymptotically efficient, and it performs similarly to the PS and PL methods in simulation experiments. The PL method appears to have a computational advantage over the PS and SL methods.

An Efficient UD-Based Algorithm for the Computation of Maximum Likelihood Sensitivity of Continuous-Discrete Systems

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...

Maximization of regional probabilities using Optimal Surface Graphs

DEFF Research Database (Denmark)

Arias Lorza, Andres M.; Van Engelen, Arna; Petersen, Jens

2018-01-01

Purpose: We present a segmentation method that maximizes regional probabilities enclosed by coupled surfaces using an Optimal Surface Graph (OSG) cut approach. This OSG cut determines the globally optimal solution given a graph constructed around an initial surface. While most methods for vessel...... wall segmentation only use edge information, we show that maximizing regional probabilities using an OSG improves the segmentation results. We applied this to automatically segment the vessel wall of the carotid artery in magnetic resonance images. Methods: First, voxel-wise regional probability maps...... were obtained using a Support Vector Machine classifier trained on local image features. Then, the OSG segments the regions which maximizes the regional probabilities considering smoothness and topological constraints. Results: The method was evaluated on 49 carotid arteries from 30 subjects...

Approximate likelihood approaches for detecting the influence of primordial gravitational waves in cosmic microwave background polarization

Science.gov (United States)

Pan, Zhen; Anderes, Ethan; Knox, Lloyd

2018-05-01

One of the major targets for next-generation cosmic microwave background (CMB) experiments is the detection of the primordial B-mode signal. Planning is under way for Stage-IV experiments that are projected to have instrumental noise small enough to make lensing and foregrounds the dominant source of uncertainty for estimating the tensor-to-scalar ratio r from polarization maps. This makes delensing a crucial part of future CMB polarization science. In this paper we present a likelihood method for estimating the tensor-to-scalar ratio r from CMB polarization observations, which combines the benefits of a full-scale likelihood approach with the tractability of the quadratic delensing technique. This method is a pixel space, all order likelihood analysis of the quadratic delensed B modes, and it essentially builds upon the quadratic delenser by taking into account all order lensing and pixel space anomalies. Its tractability relies on a crucial factorization of the pixel space covariance matrix of the polarization observations which allows one to compute the full Gaussian approximate likelihood profile, as a function of r , at the same computational cost of a single likelihood evaluation.

Efficient Computation of Entropy Gradient for Semi-Supervised Conditional Random Fields

National Research Council Canada - National Science Library

Mann, Gideon S; McCallum, Andrew

2007-01-01

Entropy regularization is a straightforward and successful method of semi-supervised learning that augments the traditional conditional likelihood objective function with an additional term that aims...

Quantifying the Establishment Likelihood of Invasive Alien Species Introductions Through Ports with Application to Honeybees in Australia.

Science.gov (United States)

Heersink, Daniel K; Caley, Peter; Paini, Dean R; Barry, Simon C

2016-05-01

The cost of an uncontrolled incursion of invasive alien species (IAS) arising from undetected entry through ports can be substantial, and knowledge of port-specific risks is needed to help allocate limited surveillance resources. Quantifying the establishment likelihood of such an incursion requires quantifying the ability of a species to enter, establish, and spread. Estimation of the approach rate of IAS into ports provides a measure of likelihood of entry. Data on the approach rate of IAS are typically sparse, and the combinations of risk factors relating to country of origin and port of arrival diverse. This presents challenges to making formal statistical inference on establishment likelihood. Here we demonstrate how these challenges can be overcome with judicious use of mixed-effects models when estimating the incursion likelihood into Australia of the European (Apis mellifera) and Asian (A. cerana) honeybees, along with the invasive parasites of biosecurity concern they host (e.g., Varroa destructor). Our results demonstrate how skewed the establishment likelihood is, with one-tenth of the ports accounting for 80% or more of the likelihood for both species. These results have been utilized by biosecurity agencies in the allocation of resources to the surveillance of maritime ports. © 2015 Society for Risk Analysis.

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 ...

Singularity Structure of Maximally Supersymmetric Scattering Amplitudes

DEFF Research Database (Denmark)

Arkani-Hamed, Nima; Bourjaily, Jacob L.; Cachazo, Freddy

2014-01-01

We present evidence that loop amplitudes in maximally supersymmetric (N=4) Yang-Mills theory (SYM) beyond the planar limit share some of the remarkable structures of the planar theory. In particular, we show that through two loops, the four-particle amplitude in full N=4 SYM has only logarithmic ...... singularities and is free of any poles at infinity—properties closely related to uniform transcendentality and the UV finiteness of the theory. We also briefly comment on implications for maximal (N=8) supergravity theory (SUGRA)....

Identities on maximal subgroups of GLn(D)

International Nuclear Information System (INIS)

Kiani, D.; Mahdavi-Hezavehi, M.

2002-04-01

Let D be a division ring with centre F. Assume that M is a maximal subgroup of GL n (D), n≥1 such that Z(M) is algebraic over F. Group identities on M and polynomial identities on the F-linear hull F[M] are investigated. It is shown that if F[M] is a PI-algebra, then [D:F] n (D) and M is a maximal subgroup of N. If M satisfies a group identity, it is shown that M is abelian-by-finite. (author)

Adaptive maximal poisson-disk sampling on surfaces

KAUST Repository

Yan, Dongming

2012-01-01

In this paper, we study the generation of maximal Poisson-disk sets with varying radii on surfaces. Based on the concepts of power diagram and regular triangulation, we present a geometric analysis of gaps in such disk sets on surfaces, which is the key ingredient of the adaptive maximal Poisson-disk sampling framework. Moreover, we adapt the presented sampling framework for remeshing applications. Several novel and efficient operators are developed for improving the sampling/meshing quality over the state-of-theart. © 2012 ACM.

The asymptotic behaviour of the maximum likelihood function of Kriging approximations using the Gaussian correlation function

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...

Is the β phase maximal?

International Nuclear Information System (INIS)

Ferrandis, Javier

2005-01-01

The current experimental determination of the absolute values of the CKM elements indicates that 2 vertical bar V ub /V cb V us vertical bar =(1-z), with z given by z=0.19+/-0.14. This fact implies that irrespective of the form of the quark Yukawa matrices, the measured value of the SM CP phase β is approximately the maximum allowed by the measured absolute values of the CKM elements. This is β=(π/6-z/3) for γ=(π/3+z/3), which implies α=π/2. Alternatively, assuming that β is exactly maximal and using the experimental measurement sin(2β)=0.726+/-0.037, the phase γ is predicted to be γ=(π/2-β)=66.3 o +/-1.7 o . The maximality of β, if confirmed by near-future experiments, may give us some clues as to the origin of CP violation

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

A New Augmentation Based Algorithm for Extracting Maximal Chordal Subgraphs.

Science.gov (United States)

Bhowmick, Sanjukta; Chen, Tzu-Yi; Halappanavar, Mahantesh

2015-02-01

A graph is chordal if every cycle of length greater than three contains an edge between non-adjacent vertices. Chordal graphs are of interest both theoretically, since they admit polynomial time solutions to a range of NP-hard graph problems, and practically, since they arise in many applications including sparse linear algebra, computer vision, and computational biology. A maximal chordal subgraph is a chordal subgraph that is not a proper subgraph of any other chordal subgraph. Existing algorithms for computing maximal chordal subgraphs depend on dynamically ordering the vertices, which is an inherently sequential process and therefore limits the algorithms' parallelizability. In this paper we explore techniques to develop a scalable parallel algorithm for extracting a maximal chordal subgraph. We demonstrate that an earlier attempt at developing a parallel algorithm may induce a non-optimal vertex ordering and is therefore not guaranteed to terminate with a maximal chordal subgraph. We then give a new algorithm that first computes and then repeatedly augments a spanning chordal subgraph. After proving that the algorithm terminates with a maximal chordal subgraph, we then demonstrate that this algorithm is more amenable to parallelization and that the parallel version also terminates with a maximal chordal subgraph. That said, the complexity of the new algorithm is higher than that of the previous parallel algorithm, although the earlier algorithm computes a chordal subgraph which is not guaranteed to be maximal. We experimented with our augmentation-based algorithm on both synthetic and real-world graphs. We provide scalability results and also explore the effect of different choices for the initial spanning chordal subgraph on both the running time and on the number of edges in the maximal chordal subgraph.

Approximate maximum parsimony and ancestral maximum likelihood.

Science.gov (United States)

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.

Study of the zero modes of the Faddeev–Popov operator in the maximal Abelian gauge

International Nuclear Information System (INIS)

Capri, M.A.L.; Guimaraes, M.S.; Lemes, V.E.R.; Sorella, S.P.; Tedesco, D.G.

2014-01-01

A study of the zero modes of the Faddeev–Popov operator in the maximal Abelian gauge is presented in the case of the gauge group SU(2) and for different Euclidean space–time dimensions. Explicit examples of classes of normalizable zero modes and corresponding gauge field configurations are constructed by taking into account two boundary conditions, namely: (i) the finite Euclidean Yang–Mills action, (ii) the finite Hilbert norm. -- Highlights: •We study the zero modes of the Faddeev–Popov operator in the maximal Abelian gauge. •For d=2 we obtain solutions with finite action but not finite Hilbert norm. •For d=3,4 we obtain solutions with finite action and finite Hilbert norm. •These results can be compared with those previously obtained in the Landau gauge

Aircraft control surface failure detection and isolation using the OSGLR test. [orthogonal series generalized likelihood ratio

Science.gov (United States)

Bonnice, W. F.; Motyka, P.; Wagner, E.; Hall, S. R.

1986-01-01

The performance of the orthogonal series generalized likelihood ratio (OSGLR) test in detecting and isolating commercial aircraft control surface and actuator failures is evaluated. A modification to incorporate age-weighting which significantly reduces the sensitivity of the algorithm to modeling errors is presented. The steady-state implementation of the algorithm based on a single linear model valid for a cruise flight condition is tested using a nonlinear aircraft simulation. A number of off-nominal no-failure flight conditions including maneuvers, nonzero flap deflections, different turbulence levels and steady winds were tested. Based on the no-failure decision functions produced by off-nominal flight conditions, the failure detection and isolation performance at the nominal flight condition was determined. The extension of the algorithm to a wider flight envelope by scheduling on dynamic pressure and flap deflection is examined. Based on this testing, the OSGLR algorithm should be capable of detecting control surface failures that would affect the safe operation of a commercial aircraft. Isolation may be difficult if there are several surfaces which produce similar effects on the aircraft. Extending the algorithm over the entire operating envelope of a commercial aircraft appears feasible.

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)

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.

Simulation-based marginal likelihood for cluster strong lensing cosmology

Science.gov (United States)

Killedar, M.; Borgani, S.; Fabjan, D.; Dolag, K.; Granato, G.; Meneghetti, M.; Planelles, S.; Ragone-Figueroa, C.

2018-01-01

Comparisons between observed and predicted strong lensing properties of galaxy clusters have been routinely used to claim either tension or consistency with Λ cold dark matter cosmology. However, standard approaches to such cosmological tests are unable to quantify the preference for one cosmology over another. We advocate approximating the relevant Bayes factor using a marginal likelihood that is based on the following summary statistic: the posterior probability distribution function for the parameters of the scaling relation between Einstein radii and cluster mass, α and β. We demonstrate, for the first time, a method of estimating the marginal likelihood using the X-ray selected z > 0.5 Massive Cluster Survey clusters as a case in point and employing both N-body and hydrodynamic simulations of clusters. We investigate the uncertainty in this estimate and consequential ability to compare competing cosmologies, which arises from incomplete descriptions of baryonic processes, discrepancies in cluster selection criteria, redshift distribution and dynamical state. The relation between triaxial cluster masses at various overdensities provides a promising alternative to the strong lensing test.

Bias Correction for the Maximum Likelihood Estimate of Ability. Research Report. ETS RR-05-15

Science.gov (United States)

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…

Parameter estimation in astronomy through application of the likelihood ratio. [satellite data analysis techniques

Science.gov (United States)

Cash, W.

1979-01-01

Many problems in the experimental estimation of parameters for models can be solved through use of the likelihood ratio test. Applications of the likelihood ratio, with particular attention to photon counting experiments, are discussed. The procedures presented solve a greater range of problems than those currently in use, yet are no more difficult to apply. The procedures are proved analytically, and examples from current problems in astronomy are discussed.

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.

Quantum speedup in solving the maximal-clique problem

Science.gov (United States)

Chang, Weng-Long; Yu, Qi; Li, Zhaokai; Chen, Jiahui; Peng, Xinhua; Feng, Mang

2018-03-01

The maximal-clique problem, to find the maximally sized clique in a given graph, is classically an NP-complete computational problem, which has potential applications ranging from electrical engineering, computational chemistry, and bioinformatics to social networks. Here we develop a quantum algorithm to solve the maximal-clique problem for any graph G with n vertices with quadratic speedup over its classical counterparts, where the time and spatial complexities are reduced to, respectively, O (√{2n}) and O (n2) . With respect to oracle-related quantum algorithms for the NP-complete problems, we identify our algorithm as optimal. To justify the feasibility of the proposed quantum algorithm, we successfully solve a typical clique problem for a graph G with two vertices and one edge by carrying out a nuclear magnetic resonance experiment involving four qubits.

Maximizing noise energy for noise-masking studies.

Science.gov (United States)

Jules Étienne, Cédric; Arleo, Angelo; Allard, Rémy

2017-08-01

Noise-masking experiments are widely used to investigate visual functions. To be useful, noise generally needs to be strong enough to noticeably impair performance, but under some conditions, noise does not impair performance even when its contrast approaches the maximal displayable limit of 100 %. To extend the usefulness of noise-masking paradigms over a wider range of conditions, the present study developed a noise with great masking strength. There are two typical ways of increasing masking strength without exceeding the limited contrast range: use binary noise instead of Gaussian noise or filter out frequencies that are not relevant to the task (i.e., which can be removed without affecting performance). The present study combined these two approaches to further increase masking strength. We show that binarizing the noise after the filtering process substantially increases the energy at frequencies within the pass-band of the filter given equated total contrast ranges. A validation experiment showed that similar performances were obtained using binarized-filtered noise and filtered noise (given equated noise energy at the frequencies within the pass-band) suggesting that the binarization operation, which substantially reduced the contrast range, had no significant impact on performance. We conclude that binarized-filtered noise (and more generally, truncated-filtered noise) can substantially increase the energy of the noise at frequencies within the pass-band. Thus, given a limited contrast range, binarized-filtered noise can display higher energy levels than Gaussian noise and thereby widen the range of conditions over which noise-masking paradigms can be useful.

Uncertainty about the true source. A note on the likelihood ratio at the activity level.

Science.gov (United States)

Taroni, Franco; Biedermann, Alex; Bozza, Silvia; Comte, Jennifer; Garbolino, Paolo

2012-07-10

This paper focuses on likelihood ratio based evaluations of fibre evidence in cases in which there is uncertainty about whether or not the reference item available for analysis - that is, an item typically taken from the suspect or seized at his home - is the item actually worn at the time of the offence. A likelihood ratio approach is proposed that, for situations in which certain categorical assumptions can be made about additionally introduced parameters, converges to formula described in existing literature. The properties of the proposed likelihood ratio approach are analysed through sensitivity analyses and discussed with respect to possible argumentative implications that arise in practice. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Multiple Improvements of Multiple Imputation Likelihood Ratio Tests

OpenAIRE

Chan, Kin Wai; Meng, Xiao-Li

2017-01-01

Multiple imputation (MI) inference handles missing data by first properly imputing the missing values $m$ times, and then combining the $m$ analysis results from applying a complete-data procedure to each of the completed datasets. However, the existing method for combining likelihood ratio tests has multiple defects: (i) the combined test statistic can be negative in practice when the reference null distribution is a standard $F$ distribution; (ii) it is not invariant to re-parametrization; ...

Muscle mitochondrial capacity exceeds maximal oxygen delivery in humans

DEFF Research Database (Denmark)

Boushel, Robert Christopher; Gnaiger, Erich; Calbet, Jose A L

2011-01-01

Across a wide range of species and body mass a close matching exists between maximal conductive oxygen delivery and mitochondrial respiratory rate. In this study we investigated in humans how closely in-vivo maximal oxygen consumption (VO(2) max) is matched to state 3 muscle mitochondrial respira...

Applying exclusion likelihoods from LHC searches to extended Higgs sectors

International Nuclear Information System (INIS)

Bechtle, Philip; Heinemeyer, Sven; Staal, Oscar; Stefaniak, Tim; Weiglein, Georg

2015-01-01

LHC searches for non-standard Higgs bosons decaying into tau lepton pairs constitute a sensitive experimental probe for physics beyond the Standard Model (BSM), such as supersymmetry (SUSY). Recently, the limits obtained from these searches have been presented by the CMS collaboration in a nearly model-independent fashion - as a narrow resonance model - based on the full 8 TeV dataset. In addition to publishing a 95 % C.L. exclusion limit, the full likelihood information for the narrowresonance model has been released. This provides valuable information that can be incorporated into global BSM fits. We present a simple algorithm that maps an arbitrary model with multiple neutral Higgs bosons onto the narrow resonance model and derives the corresponding value for the exclusion likelihood from the CMS search. This procedure has been implemented into the public computer code HiggsBounds (version 4.2.0 and higher). We validate our implementation by cross-checking against the official CMS exclusion contours in three Higgs benchmark scenarios in the Minimal Supersymmetric Standard Model (MSSM), and find very good agreement. Going beyond validation, we discuss the combined constraints of the ττ search and the rate measurements of the SM-like Higgs at 125 GeV in a recently proposed MSSM benchmark scenario, where the lightest Higgs boson obtains SM-like couplings independently of the decoupling of the heavier Higgs states. Technical details for how to access the likelihood information within HiggsBounds are given in the appendix. The program is available at http:// higgsbounds.hepforge.org. (orig.)

Theoretical Analysis of Penalized Maximum-Likelihood Patlak Parametric Image Reconstruction in Dynamic PET for Lesion Detection.

Science.gov (United States)

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.

Power calculations for likelihood ratio tests for offspring genotype risks, maternal effects, and parent-of-origin (POO) effects in the presence of missing parental genotypes when unaffected siblings are available.

Science.gov (United States)

Rampersaud, E; Morris, R W; Weinberg, C R; Speer, M C; Martin, E R

2007-01-01

Genotype-based likelihood-ratio tests (LRT) of association that examine maternal and parent-of-origin effects have been previously developed in the framework of log-linear and conditional logistic regression models. In the situation where parental genotypes are missing, the expectation-maximization (EM) algorithm has been incorporated in the log-linear approach to allow incomplete triads to contribute to the LRT. We present an extension to this model which we call the Combined_LRT that incorporates additional information from the genotypes of unaffected siblings to improve assignment of incompletely typed families to mating type categories, thereby improving inference of missing parental data. Using simulations involving a realistic array of family structures, we demonstrate the validity of the Combined_LRT under the null hypothesis of no association and provide power comparisons under varying levels of missing data and using sibling genotype data. We demonstrate the improved power of the Combined_LRT compared with the family-based association test (FBAT), another widely used association test. Lastly, we apply the Combined_LRT to a candidate gene analysis in Autism families, some of which have missing parental genotypes. We conclude that the proposed log-linear model will be an important tool for future candidate gene studies, for many complex diseases where unaffected siblings can often be ascertained and where epigenetic factors such as imprinting may play a role in disease etiology.

Existence and uniqueness of the maximum likelihood estimator for models with a Kronecker product covariance structure

NARCIS (Netherlands)

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

Procrastination in the pigeon: Can conditioned reinforcement increase the likelihood of human procrastination?

Science.gov (United States)

Zentall, Thomas R; Case, Jacob P; Andrews, Danielle M

2017-11-29

Procrastination is the tendency to put off initiation or completion of a task. Although people are typically known to procrastinate, recent research suggests that they sometimes "pre-crastinate" by initiating a task sooner than they need to (Rosenbaum et al. in Psychological Science, 25(7), 1487-1496, 2014). A similar finding of precrastination was reported by Wasserman and Brzykcy (Psychonomic Bulletin & Review, 22, 1130-1134, 2015) with pigeons using a somewhat different procedure. In the present experiment, we used a procedure with pigeons that was more similar to the procedure used by Rosenbaum et al. Pigeons were given a choice between two sequences of events (concurrent chains). Choice of the procrastination chain resulted in color A, which 15-s later would change to color B and 5-s later resulted in reinforcement. Choice of the precrastination chain resulted in color C, which 5-s later would change to color D and 15-s later resulted in reinforcement. Thus, both chains led to reinforcement after 20 s. Results indicated that the pigeons procrastinated. That is, they preferred the 15-5 chain over the 5-15 chain. The results are consistent with Fantino's (Journal of the Experimental Analysis of Behavior, 12, 723-730, 1969) delay reduction theory, which posits that stimuli that signal a reduction in the delay to reinforcement, such as the 5-s stimulus that occurred immediately prior to reinforcement, serve as strong conditioned reinforcers and should be preferred. In support of this theory, the pigeons pecked most at the 5-s stimulus that led immediately to reinforcement, indicating that it had become a strong conditioned reinforcer. The results suggest that delay reduction theory, a theory that emphasizes the attraction to stimuli that predict reinforcement with a short delay, also may contribute to human procrastination behavior because when task completion comes just before the deadline, it may become a stronger conditioned reinforcer than if task completion

Stochastic conditional intensity processes

DEFF Research Database (Denmark)

Bauwens, Luc; Hautsch, Nikolaus

2006-01-01

model allows for a wide range of (cross-)autocorrelation structures in multivariate point processes. The model is estimated by simulated maximum likelihood (SML) using the efficient importance sampling (EIS) technique. By modeling price intensities based on NYSE trading, we provide significant evidence......In this article, we introduce the so-called stochastic conditional intensity (SCI) model by extending Russell’s (1999) autoregressive conditional intensity (ACI) model by a latent common dynamic factor that jointly drives the individual intensity components. We show by simulations that the proposed...... for a joint latent factor and show that its inclusion allows for an improved and more parsimonious specification of the multivariate intensity process...

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...

Optimizing Half Squat Postactivation Potential Load in Squat Jump Training for Eliciting Relative Maximal Power in Ski Jumpers.

Science.gov (United States)

Gołaś, Artur; Wilk, Michal; Stastny, Petr; Maszczyk, Adam; Pajerska, Katarzyna; Zając, Adam

2017-11-01

Gołaś, A, Wilk, M, Stastny, P, Maszczyk, A, Pajerska, K, and Zając, A. Optimizing half squat postactivation potential load in squat jump training for eliciting relative maximal power in ski jumpers. J Strength Cond Res 31(11): 3010-3017, 2017-Training load manipulation in a single workout session can increase or decrease training effectiveness in terms of athletes' strength or power gains. In ski jumping, the complex training that elicits maximal power gains may take advantage of the postactivation potentiation (PAP) mechanism. The aim of this research was to evaluate the changes in rate of force development (RFD), rate of power development (RPD), and jump height during a complex training session consisted of the barbell half squat (Sq) as a conditioning exercise with loads ranged between 60 and 100% of 1 repetition maximum (1RM), followed by a body weight squat jump (SqJ) as a performance task. The study was conducted with 16 elite athletes from the Polish National Ski Jumping Team, age 23 ± 8 years, body mass 56 ± 9 kg, and height 172 ± 12 cm. Complex training session started with the Sq at 60% of 1RM as the conditioning exercise, followed by 3 minutes of rest and the SqJ. The conditioning barbell half Sq was performed with 70, 80, 90, and 100% of 1RM with 5 minutes of rest. The differences in RFD occurred between an SqJ following the application of 80% of 1RM and all other SqJs (p = 0.01), and in RPD between SqJ without conditioning, SqJ after 60% of 1RM and 80% of 1RM (p = 0.02). On average, the most effective load in inducing PAP during ski jumpers' SqJ training is 80% of 1RM. The intensity of the conditioning exercise that elicits the greatest PAP effect should be individualized (60-100% 1RM), as it is dependent on the level of maximal strength.

Enumerating all maximal frequent subtrees in collections of phylogenetic trees.

Science.gov (United States)

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.

Softly Broken Lepton Numbers: an Approach to Maximal Neutrino Mixing

International Nuclear Information System (INIS)

Grimus, W.; Lavoura, L.

2001-01-01

We discuss models where the U(1) symmetries of lepton numbers are responsible for maximal neutrino mixing. We pay particular attention to an extension of the Standard Model (SM) with three right-handed neutrino singlets in which we require that the three lepton numbers L e , L μ , and L τ be separately conserved in the Yukawa couplings, but assume that they are softly broken by the Majorana mass matrix M R of the neutrino singlets. In this framework, where lepton-number breaking occurs at a scale much higher than the electroweak scale, deviations from family lepton number conservation are calculable, i.e., finite, and lepton mixing stems exclusively from M R . We show that in this framework either maximal atmospheric neutrino mixing or maximal solar neutrino mixing or both can be imposed by invoking symmetries. In this way those maximal mixings are stable against radiative corrections. The model which achieves maximal (or nearly maximal) solar neutrino mixing assumes that there are two different scales in M R and that the lepton number (dash)L=L e -L μ -L τ 1 is conserved in between them. We work out the difference between this model and the conventional scenario where (approximate) (dash)L invariance is imposed directly on the mass matrix of the light neutrinos. (author)

Cointegration rank testing under conditional heteroskedasticity

DEFF Research Database (Denmark)

Cavaliere, Giuseppe; Rahbek, Anders Christian; Taylor, Robert M.

2010-01-01

We analyze the properties of the conventional Gaussian-based cointegrating rank tests of Johansen (1996, Likelihood-Based Inference in Cointegrated Vector Autoregressive Models) in the case where the vector of series under test is driven by globally stationary, conditionally heteroskedastic......, relative to tests based on the asymptotic critical values or the i.i.d. bootstrap, the wild bootstrap rank tests perform very well in small samples under a variety of conditionally heteroskedastic innovation processes. An empirical application to the term structure of interest rates is given....

Derivation of LDA log likelihood ratio one-to-one classifier

NARCIS (Netherlands)

Spreeuwers, Lieuwe Jan

2014-01-01

The common expression for the Likelihood Ratio classifier using LDA assumes that the reference class mean is available. In biometrics, this is often not the case and only a single sample of the reference class is available. In this paper expressions are derived for biometric comparison between

Counseling Pretreatment and the Elaboration Likelihood Model of Attitude Change.

Science.gov (United States)

Heesacker, Martin

1986-01-01

Results of the application of the Elaboration Likelihood Model (ELM) to a counseling context revealed that more favorable attitudes toward counseling occurred as subjects' ego involvement increased and as intervention quality improved. Counselor credibility affected the degree to which subjects' attitudes reflected argument quality differences.…

Efficient estimators for likelihood ratio sensitivity indices of complex stochastic dynamics

Energy Technology Data Exchange (ETDEWEB)

Arampatzis, Georgios; Katsoulakis, Markos A.; Rey-Bellet, Luc [Department of Mathematics and Statistics, University of Massachusetts, Amherst, Massachusetts 01003 (United States)

2016-03-14

We demonstrate that centered likelihood ratio estimators for the sensitivity indices of complex stochastic dynamics are highly efficient with low, constant in time variance and consequently they are suitable for sensitivity analysis in long-time and steady-state regimes. These estimators rely on a new covariance formulation of the likelihood ratio that includes as a submatrix a Fisher information matrix for stochastic dynamics and can also be used for fast screening of insensitive parameters and parameter combinations. The proposed methods are applicable to broad classes of stochastic dynamics such as chemical reaction networks, Langevin-type equations and stochastic models in finance, including systems with a high dimensional parameter space and/or disparate decorrelation times between different observables. Furthermore, they are simple to implement as a standard observable in any existing simulation algorithm without additional modifications.

Likelihood updating of random process load and resistance parameters by monitoring

DEFF Research Database (Denmark)

Friis-Hansen, Peter; Ditlevsen, Ove Dalager

2003-01-01

that maximum likelihood estimation is a rational alternative to an arbitrary weighting for least square fitting. The derived likelihood function gets singularities if the spectrum is prescribed with zero values at some frequencies. This is often the case for models of technically relevant processes......, even though it is of complicated mathematical form, allows an approximate Bayesian updating and control of the time development of the parameters. Some of these parameters can be structural parameters that by too much change reveal progressing damage or other malfunctioning. Thus current process......Spectral parameters for a stationary Gaussian process are most often estimated by Fourier transformation of a realization followed by some smoothing procedure. This smoothing is often a weighted least square fitting of some prespecified parametric form of the spectrum. In this paper it is shown...

Menyoal Elaboration Likelihood Model (ELM) dan Teori Retorika

OpenAIRE

Yudi Perbawaningsih

2012-01-01

Abstract: Persuasion is a communication process to establish or change attitudes, which can be understood through theory of Rhetoric and theory of Elaboration Likelihood Model (ELM). This study elaborates these theories in a Public Lecture series which to persuade the students in choosing their concentration of study. The result shows that in term of persuasion effectiveness it is not quite relevant to separate the message and its source. The quality of source is determined by the quality of ...

Menyoal Elaboration Likelihood Model (ELM) Dan Teori Retorika

OpenAIRE

Perbawaningsih, Yudi

2012-01-01

: Persuasion is a communication process to establish or change attitudes, which can be understood through theory of Rhetoric and theory of Elaboration Likelihood Model (ELM). This study elaborates these theories in a Public Lecture series which to persuade the students in choosing their concentration of study. The result shows that in term of persuasion effectiveness it is not quite relevant to separate the message and its source. The quality of source is determined by the quality of the mess...

Democracy, Autocracy and the Likelihood of International Conflict

OpenAIRE

Tangerås, Thomas

2008-01-01

This is a game-theoretic analysis of the link between regime type and international conflict. The democratic electorate can credibly punish the leader for bad conflict outcomes, whereas the autocratic selectorate cannot. For the fear of being thrown out of office, democratic leaders are (i) more selective about the wars they initiate and (ii) on average win more of the wars they start. Foreign policy behaviour is found to display strategic complementarities. The likelihood of interstate war, ...

Maximal heart rate does not limit cardiovascular capacity in healthy humans

DEFF Research Database (Denmark)

Munch, G D W; Svendsen, J H; Damsgaard, R

2014-01-01

In humans, maximal aerobic power (VO2 max ) is associated with a plateau in cardiac output (Q), but the mechanisms regulating the interplay between maximal heart rate (HRmax) and stroke volume (SV) are unclear. To evaluate the effect of tachycardia and elevations in HRmax on cardiovascular function...... and capacity during maximal exercise in healthy humans, 12 young male cyclists performed incremental cycling and one-legged knee-extensor exercise (KEE) to exhaustion with and without right atrial pacing to increase HR. During control cycling, Q and leg blood flow increased up to 85% of maximal workload (WLmax...... and RAP (P healthy...

Power Converters Maximize Outputs Of Solar Cell Strings

Science.gov (United States)

Frederick, Martin E.; Jermakian, Joel B.

1993-01-01

Microprocessor-controlled dc-to-dc power converters devised to maximize power transferred from solar photovoltaic strings to storage batteries and other electrical loads. Converters help in utilizing large solar photovoltaic arrays most effectively with respect to cost, size, and weight. Main points of invention are: single controller used to control and optimize any number of "dumb" tracker units and strings independently; power maximized out of converters; and controller in system is microprocessor.

No Mikheyev-Smirnov-Wolfenstein Effect in Maximal Mixing

OpenAIRE

Harrison, P. F.; Perkins, D. H.; Scott, W. G.

1996-01-01

We investigate the possible influence of the MSW effect on the expectations for the solar neutrino experiments in the maximal mixing scenario suggested by the atmospheric neutrino data. A direct numerical calculation of matter induced effects in the Sun shows that the naive vacuum predictions are left completely undisturbed in the particular case of maximal mixing, so that the MSW effect turns out to be unobservable. We give a qualitative explanation of this result.

Single maximal versus combination punch kinematics.

Science.gov (United States)

Piorkowski, Barry A; Lees, Adrian; Barton, Gabor J

2011-03-01

The aim of this study was to determine the influence of punch type (Jab, Cross, Lead Hook and Reverse Hook) and punch modality (Single maximal, 'In-synch' and 'Out of synch' combination) on punch speed and delivery time. Ten competition-standard volunteers performed punches with markers placed on their anatomical landmarks for 3D motion capture with an eight-camera optoelectronic system. Speed and duration between key moments were computed. There were significant differences in contact speed between punch types (F(2,18,84.87) = 105.76, p = 0.001) with Lead and Reverse Hooks developing greater speed than Jab and Cross. There were significant differences in contact speed between punch modalities (F(2,64,102.87) = 23.52, p = 0.001) with the Single maximal (M+/- SD: 9.26 +/- 2.09 m/s) higher than 'Out of synch' (7.49 +/- 2.32 m/s), 'In-synch' left (8.01 +/- 2.35 m/s) or right lead (7.97 +/- 2.53 m/s). Delivery times were significantly lower for Jab and Cross than Hook. Times were significantly lower 'In-synch' than a Single maximal or 'Out of synch' combination mode. It is concluded that a defender may have more evasion-time than previously reported. This research could be of use to performers and coaches when considering training preparations.

Formation Control for the MAXIM Mission

Science.gov (United States)

Luquette, Richard J.; Leitner, Jesse; Gendreau, Keith; Sanner, Robert M.

2004-01-01

Over the next twenty years, a wave of change is occurring in the space-based scientific remote sensing community. While the fundamental limits in the spatial and angular resolution achievable in spacecraft have been reached, based on today s technology, an expansive new technology base has appeared over the past decade in the area of Distributed Space Systems (DSS). A key subset of the DSS technology area is that which covers precision formation flying of space vehicles. Through precision formation flying, the baselines, previously defined by the largest monolithic structure which could fit in the largest launch vehicle fairing, are now virtually unlimited. Several missions including the Micro-Arcsecond X-ray Imaging Mission (MAXIM), and the Stellar Imager will drive the formation flying challenges to achieve unprecedented baselines for high resolution, extended-scene, interferometry in the ultraviolet and X-ray regimes. This paper focuses on establishing the feasibility for the formation control of the MAXIM mission. MAXIM formation flying requirements are on the order of microns, while Stellar Imager mission requirements are on the order of nanometers. This paper specifically addresses: (1) high-level science requirements for these missions and how they evolve into engineering requirements; and (2) the development of linearized equations of relative motion for a formation operating in an n-body gravitational field. Linearized equations of motion provide the ground work for linear formation control designs.

Conversational Implicature of Peanuts Comic Strip Based on Grice’s Maxim Theory

Directory of Open Access Journals (Sweden)

Muhartoyo Muhartoyo

2013-04-01

Full Text Available This article discusses about conversational implicature that occurs in Peanuts comic strips. The objectives of this study are to find out the implied meaning in the conversation between Charlie Brown with Lucy van Pelt and Lucy van Pelt with Linus van Pelt to evaluate the existence of maxim flouting and maxim violating in those conversations in relation to the four maxims such as quantity, quality, relation, and manner. Likewise, this study attempts to find out the reason for using conversational implicature in a comic strip. The writers uses a qualitative method with library research concerning to Grice’s maxim theory to analyze the conversational implicature. Based on the analysis, it can be concluded that all the comics that comprise 14 comics generate conversational implicature since all the characters breach rules of maxim. The result of this analysis shows that flouting maxim of manner has the highest occurrence of conversational implicature and the least occurrences belong to flouting maxim of relation and violating maxim of quantity. Moreover, the writers concludes that to make a successful communication ideally the speaker and the hearer to cooperate in the conversation by saying explicitly so the hearer can grasp the meaning as the goal of communication is to deliver a message to the hearer.  

Sociodemographic disparities in the occurrence of medical conditions among adolescent and young adult Hodgkin lymphoma survivors.

Science.gov (United States)

Keegan, Theresa H M; Li, Qian; Steele, Amy; Alvarez, Elysia M; Brunson, Ann; Flowers, Christopher R; Glaser, Sally L; Wun, Ted

2018-06-01

Hodgkin lymphoma (HL) survivors experience high risks of second cancers and cardiovascular disease, but no studies have considered whether the occurrence of these and other medical conditions differ by sociodemographic factors in adolescent and young adult (AYA) survivors. Data for 5,085 patients aged 15-39 when diagnosed with HL during 1996-2012 and surviving ≥ 2 years were obtained from the California Cancer Registry and linked to hospitalization data. We examined the impact of race/ethnicity, neighborhood socioeconomic status (SES), and health insurance on the occurrence of medical conditions (≥ 2 years after diagnosis) and the impact of medical conditions on survival using multivariable Cox proportional hazards regression. Twenty-six percent of AYAs experienced at least one medical condition and 15% had ≥ 2 medical conditions after treatment for HL. In multivariable analyses, Black HL survivors had a higher likelihood (vs. non-Hispanic Whites) of endocrine [hazard ratio (HR) = 1.37, 95% confidence interval (CI) 1.05-1.78] and circulatory system diseases (HR = 1.58, CI 1.17-2.14); Hispanics had a higher likelihood of endocrine diseases [HR = 1.24 (1.04-1.48)]. AYAs with public or no insurance (vs. private/military) had higher likelihood of circulatory system diseases, respiratory system diseases, chronic kidney disease/renal failure, liver disease, and endocrine diseases. AYAs residing in low SES neighborhoods (vs. high) had higher likelihood of respiratory system and endocrine diseases. AYAs with these medical conditions or second cancers had an over twofold increased risk of death. Strategies to improve health care utilization for surveillance and secondary prevention among AYA HL survivors at increased risk of medical conditions may improve outcomes.

Comparison of changes in the mobility of the pelvic floor muscle on during the abdominal drawing-in maneuver, maximal expiration, and pelvic floor muscle maximal contraction.

Science.gov (United States)

Jung, Halim; Jung, Sangwoo; Joo, Sunghee; Song, Changho

2016-01-01

[Purpose] The purpose of this study was to compare changes in the mobility of the pelvic floor muscle during the abdominal drawing-in maneuver, maximal expiration, and pelvic floor muscle maximal contraction. [Subjects] Thirty healthy adults participated in this study (15 men and 15 women). [Methods] All participants performed a bridge exercise and abdominal curl-up during the abdominal drawing-in maneuver, maximal expiration, and pelvic floor muscle maximal contraction. Pelvic floor mobility was evaluated as the distance from the bladder base using ultrasound. [Results] According to exercise method, bridge exercise and abdominal curl-ups led to significantly different pelvic floor mobility. The pelvic floor muscle was elevated during the abdominal drawing-in maneuver and descended during maximal expiration. Finally, pelvic floor muscle mobility was greater during abdominal curl-up than during the bridge exercise. [Conclusion] According to these results, the abdominal drawing-in maneuver induced pelvic floor muscle contraction, and pelvic floor muscle contraction was greater during the abdominal curl-up than during the bridge exercise.

Descriptive Analysis on Flouting and Hedging of Conversational Maxims in the “Post Grad” Movie

Directory of Open Access Journals (Sweden)

Nastiti Rokhmania

2012-11-01

Full Text Available This research is focused on analyzing flouting and hedging of conversational maxim of utterances used by the main characters in “Post Grad” movie. Conversational maxims are the rules of cooperative principle categorized into four categories; Maxim of Quality, Maxim of Quantity, Maxim of Relevance, and Maxim of Manner. If these maxims are used in conversations, the conversations can go smoothly. However, people often break the maxims overtly (flouting maxim and sometimes break the maxims secretly (hedging maxims when they make a conversation. This research is conducted using descriptive qualitative method based on the theory known as Grice’s Maxims. The data are in form of utterances used by the characters in “Post Grad” movie. The data analysis reveals some finding covering the formulated research question. The maxims are flouted when the speaker breaks some conversational maxims when using the utterances in the form of rhetorical strategies, such as tautology, metaphor, hyperbole, irony, and rhetorical question. On the other hand, conversational maxims are also hedged when the information is not totally accurate or unclearly stated but seems informative, well-founded, and relevant.

Robust Likelihoods for Inflationary Gravitational Waves from Maps of Cosmic Microwave Background Polarization

Science.gov (United States)

Switzer, Eric Ryan; Watts, Duncan J.

2016-01-01

The B-mode polarization of the cosmic microwave background provides a unique window into tensor perturbations from inflationary gravitational waves. Survey effects complicate the estimation and description of the power spectrum on the largest angular scales. The pixel-space likelihood yields parameter distributions without the power spectrum as an intermediate step, but it does not have the large suite of tests available to power spectral methods. Searches for primordial B-modes must rigorously reject and rule out contamination. Many forms of contamination vary or are uncorrelated across epochs, frequencies, surveys, or other data treatment subsets. The cross power and the power spectrum of the difference of subset maps provide approaches to reject and isolate excess variance. We develop an analogous joint pixel-space likelihood. Contamination not modeled in the likelihood produces parameter-dependent bias and complicates the interpretation of the difference map. We describe a null test that consistently weights the difference map. Excess variance should either be explicitly modeled in the covariance or be removed through reprocessing the data.

A simplification of the likelihood ratio test statistic for testing ...

African Journals Online (AJOL)

The traditional likelihood ratio test statistic for testing hypothesis about goodness of fit of multinomial probabilities in one, two and multi – dimensional contingency table was simplified. Advantageously, using the simplified version of the statistic to test the null hypothesis is easier and faster because calculating the expected ...

A Game Theoretical Approach to Hacktivism: Is Attack Likelihood a Product of Risks and Payoffs?

Science.gov (United States)

Bodford, Jessica E; Kwan, Virginia S Y

2018-02-01

The current study examines hacktivism (i.e., hacking to convey a moral, ethical, or social justice message) through a general game theoretic framework-that is, as a product of costs and benefits. Given the inherent risk of carrying out a hacktivist attack (e.g., legal action, imprisonment), it would be rational for the user to weigh these risks against perceived benefits of carrying out the attack. As such, we examined computer science students' estimations of risks, payoffs, and attack likelihood through a game theoretic design. Furthermore, this study aims at constructing a descriptive profile of potential hacktivists, exploring two predicted covariates of attack decision making, namely, peer prevalence of hacking and sex differences. Contrary to expectations, results suggest that participants' estimations of attack likelihood stemmed solely from expected payoffs, rather than subjective risks. Peer prevalence significantly predicted increased payoffs and attack likelihood, suggesting an underlying descriptive norm in social networks. Notably, we observed no sex differences in the decision to attack, nor in the factors predicting attack likelihood. Implications for policymakers and the understanding and prevention of hacktivism are discussed, as are the possible ramifications of widely communicated payoffs over potential risks in hacking communities.

Maximal and anaerobic threshold cardiorespiratory responses during deepwater running

Directory of Open Access Journals (Sweden)

Ana Carolina Kanitz

2014-12-01

Full Text Available DOI: http://dx.doi.org/10.5007/1980-0037.2015v17n1p41   Aquatic exercises provide numerous benefits to the health of their practitioners. To secure these benefits, it is essential to have proper prescriptions to the needs of each individual and, therefore, it is important to study the cardiorespiratory responses of different activities in this environment. Thus, the aim of this study was to compare the cardiorespiratory responses at the anaerobic threshold (AT between maximal deep-water running (DWR and maximal treadmill running (TMR. In addition, two methods of determining the AT (the heart rate deflection point [HRDP] and ventilatory method [VM] are compared in the two evaluated protocols. Twelve young women performed the two maximal protocols. Two-factor ANOVA for repeated measures with a post-hoc Bonferroni test was used (α < 0.05. Significantly higher values of maximal heart rate (TMR: 33.7 ± 3.9; DWR: 22.5 ± 4.1 ml.kg−1.min−1 and maximal oxygen uptake (TMR: 33.7 ± 3.9; DWR: 22.5 ± 4.1 ml.kg−1.min−1 in TMR compared to the DWR were found. Furthermore, no significant differences were found between the methods for determining the AT (TMR: VM: 28.1 ± 5.3, HRDP: 26.6 ± 5.5 ml.kg−1.min−1; DWR: VM: 18.7 ± 4.8, HRDP: 17.8 ± 4.8 ml.kg−1.min−1. The results indicate that a specific maximal test for the trained modality should be conducted and the HRDP can be used as a simple and practical method of determining the AT, based on which the training intensity can be determined

Likelihood-Based Inference of B Cell Clonal Families.

Directory of Open Access Journals (Sweden)

Duncan K Ralph

2016-10-01

Full Text Available The human immune system depends on a highly diverse collection of antibody-making B cells. B cell receptor sequence diversity is generated by a random recombination process called "rearrangement" forming progenitor B cells, then a Darwinian process of lineage diversification and selection called "affinity maturation." The resulting receptors can be sequenced in high throughput for research and diagnostics. Such a collection of sequences contains a mixture of various lineages, each of which may be quite numerous, or may consist of only a single member. As a step to understanding the process and result of this diversification, one may wish to reconstruct lineage membership, i.e. to cluster sampled sequences according to which came from the same rearrangement events. We call this clustering problem "clonal family inference." In this paper we describe and validate a likelihood-based framework for clonal family inference based on a multi-hidden Markov Model (multi-HMM framework for B cell receptor sequences. We describe an agglomerative algorithm to find a maximum likelihood clustering, two approximate algorithms with various trade-offs of speed versus accuracy, and a third, fast algorithm for finding specific lineages. We show that under simulation these algorithms greatly improve upon existing clonal family inference methods, and that they also give significantly different clusters than previous methods when applied to two real data sets.

Quantization with maximally degenerate Poisson brackets: the harmonic oscillator!

International Nuclear Information System (INIS)

Nutku, Yavuz

2003-01-01

Nambu's construction of multi-linear brackets for super-integrable systems can be thought of as degenerate Poisson brackets with a maximal set of Casimirs in their kernel. By introducing privileged coordinates in phase space these degenerate Poisson brackets are brought to the form of Heisenberg's equations. We propose a definition for constructing quantum operators for classical functions, which enables us to turn the maximally degenerate Poisson brackets into operators. They pose a set of eigenvalue problems for a new state vector. The requirement of the single-valuedness of this eigenfunction leads to quantization. The example of the harmonic oscillator is used to illustrate this general procedure for quantizing a class of maximally super-integrable systems

Rapid maximum likelihood ancestral state reconstruction of continuous characters: A rerooting-free algorithm.

Science.gov (United States)

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

A biclustering algorithm for binary matrices based on penalized Bernoulli likelihood

KAUST Repository

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

On Maximally Dissipative Shock Waves in Nonlinear Elasticity

OpenAIRE

Knowles, James K.

2010-01-01

Shock waves in nonlinearly elastic solids are, in general, dissipative. We study the following question: among all plane shock waves that can propagate with a given speed in a given one-dimensional nonlinearly elastic bar, which one—if any—maximizes the rate of dissipation? We find that the answer to this question depends strongly on the qualitative nature of the stress-strain relation characteristic of the given material. When maximally dissipative shocks do occur, they propagate according t...

The Large Margin Mechanism for Differentially Private Maximization

OpenAIRE

Chaudhuri, Kamalika; Hsu, Daniel; Song, Shuang

2014-01-01

A basic problem in the design of privacy-preserving algorithms is the private maximization problem: the goal is to pick an item from a universe that (approximately) maximizes a data-dependent function, all under the constraint of differential privacy. This problem has been used as a sub-routine in many privacy-preserving algorithms for statistics and machine-learning. Previous algorithms for this problem are either range-dependent---i.e., their utility diminishes with the size of the universe...

Coalescent-based species tree inference from gene tree topologies under incomplete lineage sorting by maximum likelihood.

Science.gov (United States)

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.

Modified Moment, Maximum Likelihood and Percentile Estimators for the Parameters of the Power Function Distribution

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.

Enumerating all maximal frequent subtrees in collections of phylogenetic trees

Science.gov (United States)

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

Maximizing performance in supercritical fluid chromatography using low-density mobile phases.

Science.gov (United States)

Gritti, Fabrice; Fogwill, Michael; Gilar, Martin; Jarrell, Joseph A

2016-10-14

The performance of a 3.0mm×150mm column packed with 1.8μm fully porous HSS-SB-C 18 particles was investigated in supercritical fluid chromatography (SFC) with low-density, highly expansible carbon dioxide. These conditions are selected for the analysis of semi-volatile compounds. Elevated temperatures (>100°C) were then combined with low column back pressures (<100bar). In this work, the inlet temperature of pure carbon dioxide was set at 107°C, the active back pressure regulator (ABPR) pressure was fixed at 100bar, and the flow rate was set at 2.1mL/min at 12°C (liquefied carbon dioxide) and at an inlet column pressure close to 300bar. Nine n-alkylbenzenes (from benzene to octadecylbenzene) were injected under linear (no sample overload) conditions. The severe steepness of the temperature gradients across the column diameter were predicted from a simplified heat transfer model. Such conditions dramatically lower the column performance by affecting the symmetry of the peak shape. In order to cope with this problem, three different approaches were experimentally tested. They include (1) the decoupling and the proper selection of the inlet eluent temperature with respect to the oven temperature, (2) the partial thermal insulation of the column using polyethylene aerogel, and (3) the application of a high vacuum (10 -5 Torr provided by a turbo-molecular pump) in a housing chamber surrounding the whole column body. The results reveal that (1) the column efficiency can be maximized by properly selecting the difference between the eluent and the oven temperatures, (2) the mere wrapping of the column with an excellent insulating material is insufficient to fully eliminate heat exchanges by conduction and the undesirable radial density gradients across the column i.d., and (3) the complete thermal insulation of the SFC column under high vacuum allows to maximize the column efficiency by maintaining the integrity of the peak shape. Copyright © 2016 Elsevier B.V. All

Pace's Maxims for Homegrown Library Projects. Coming Full Circle

Science.gov (United States)

Pace, Andrew K.

2005-01-01

This article discusses six maxims by which to run library automation. The following maxims are discussed: (1) Solve only known problems; (2) Avoid changing data to fix display problems; (3) Aut viam inveniam aut faciam; (4) If you cannot make it yourself, buy something; (5) Kill the alligator closest to the boat; and (6) Just because yours is…

Failed refutations: further comments on parsimony and likelihood methods and their relationship to Popper's degree of corroboration.

Science.gov (United States)

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