salmo salar bayesian: Topics by WorldWideScience.org

Bayesian Mediation Analysis

BackgroundExpansion of aquaculture is seriously limited by reductions in fish oil (FO) supply for aquafeeds. Terrestrial alternatives such as vegetable oils (VO) have been investigated...Full Text Available

Extended amino acid sequences around the active-site lysine residue of class-I fructose 1,6-bisphosphate aldolases from rabbit muscle, sturgeon muscle, trout muscle and ox liver.

This article proposes Bayesian analysis of mediation effects. Compared to conventional frequentist mediation analysis, the Bayesian approach has several advantages. First, it allows researchers...Full Text Available

2009-12-01

Bayesian Cue Integration as a Developmental Outcome of Reward Mediated Learning

1. Amino acid sequences covering the region between residues 173 and 248 [adopting the numbering system proposed by Lai, Nakai & Chang (1974) Science 183, 1204-1206] were derived for trout (Salmo...Full Text Available

1979-11-01

Bayesian estimation of mixed Weibull distributions

Average human behavior in cue combination tasks is well predicted by Bayesian inference models. As this capability is acquired over developmental timescales, the question arises, how it is learned....Full Text Available

Radiological Source Localisation

Estimation of mixed Weibull distribution by maximum likelihood estimation and other methods is frequently difficult due to unstable estimates arising from limited data. Bayesian techniques can stabilize these estimates through the priors, but there is no closed-form conjugate family for the Weibull distribution. This paper reduces the number of numeric integrations required for using Bayesian estimation on mixed Weibull situations from five to two, thus making it a more feasible approach to the typical user. It also examines the robustness of the Bayesian estimates under a variety of different prior distributions. It is found that Bayesian estimation can improve accuracy over the MLE for situations with low mixture ratios so long as the prior on the weak subpopulation's characteristic life has an expected value less than or equal to the true characteristic life.

2009-02-15

Bayesian models for multiple outcomes nested in domains

... The goal of filtering (the sequential Bayesian ... 5] and the unscented Kalman filter (UKF) [16 ... set of deterministically chosen sample (or sigma) points. ...

2007-07-01

Estimating a parameter of Burr type XII distribution using hybrid censored observations

SummaryWe consider the problem of estimating the effect of exposure on multiple continuous outcomes, when the outcomes are measured on different scales and are nested within multiple...Full Text Available

2009-12-01

British Library Electronic Table of Contents (United Kingdom)

Purpose - Burr distribution has been proved to be a useful failure model. It can assume different shapes which allow it to be a good fit for various lifetimes data. Hybrid censoring is an important way of generating lifetimes data. The purpose of this paper is to estimate an unknown parameter of the Burr type XII distribution when data are hybrid censored. Design/methodology/approach - The problem is dealt with through both the classical and Bayesian point of view. Specifically, the methods of estimation used to tackle the problem are maximum likelihood estimation method and Bayesian method. Empirical Bayesian approach is also considered. The performance of all estimates is compared through their mean square error values. The paper employs Monte Carlo simulation to evaluate the mean square...

2011-01-01

Development of an internet based system for modeling biotin metabolism using Bayesian networks

British Library Electronic Table of Contents (United Kingdom)

Biotin is an essential water-soluble vitamin crucial for maintaining normal body functions. The importance of biotin for human health has been under-appreciated but there is plenty of opportunity for future research with great importance for human health. Currently, carrying out predictions of biotin metabolism involves tedious manual manipulations. In this paper, we report the development of BiotinNet, an internet based program that uses Bayesian networks to integrate published data on various aspects of biotin metabolism. Users can provide a combination of values on the levels of biotin related metabolites to obtain the predictions on other metabolites that are not specified. As an inherent feature of Bayesian networks, the uncertainty of the prediction is also quantified and reported to...

2011-01-01

Cosmological model selection

Selected results in hadron structure from lattice QCD

Model selection aims to determine which theoretical models are most plausible given some data, without necessarily asking about the preferred values of the model parameters. A common model selection question is to ask when new data require introduction of an additional parameter, describing a newly-discovered physical effect. We review several model selection statistics, and then focus on use of the Bayesian evidence, which implements the usual Bayesian analysis framework at the level of models rather than parameters. We describe our CosmoNest code, which is the first computationally-efficient implementation of Bayesian model selection in a cosmological context. We apply it to recent WMAP satellite data, examining the need for a perturbation spectral index differing from the scale-invariant (Harrison-Zel'dovich) case.

2006-01-01

Selected results in hadron structure from lattice QCD

I present results for the mass spectrum of excited baryons and pentaquarks using overlap fermions and Bayesian curve-fitting method; and magnetic moments and polarizabilities for a variety of hadrons in the background field method.

2006-03-15

Nonlinear Bayesian Algorithms for Gas Plume Detection and Estimation from Hyper-spectral Thermal Image Data

2006-03-01

Measuring quality of care in psychiatric emergencies: construction and evaluation of a Bayesian index.

This paper presents a nonlinear Bayesian regression algorithm for the purpose of detecting and estimating gas plume content from hyper-spectral data. Remote sensing data, by its very nature, is collected under less controlled conditions than laboratory data. As a result, the physics-based model that is used to describe the relationship between the observed remotesensing spectra, and the terrestrial (or atmospheric) parameters that we desire to estimate, is typically littered with many unknown "nuisance" parameters (parameters that we are not interested in estimating, but also appear in the model). Bayesian methods are well-suited for this context as they automatically incorporate the uncertainties associated with all nuisance parameters into the error estimates of the parameters of interest. The nonlinear Bayesian regression methodology is illustrated on realistic simulated data from a three-layer model for longwave ...

2007-06-13

Fast, Scalable, Bayesian Spike Identification for Multi-Electrode Arrays

OBJECTIVE. This study was conducted to determine whether an index for measuring quality of care for psychiatric emergencies is reliable and valid. DATA SOURCES/STUDY SETTING. The study used primary...Full Text Available

1993-06-01

Age-Stratified Bayesian Analysis To Estimate Sensitivity and Specificity of Four Diagnostic Tests for Detection of Cryptosporidium Oocysts in Neonatal Calves?

We present an algorithm to identify individual neural spikes observed on high-density multi-electrode arrays (MEAs). Our method can distinguish large numbers of distinct neural units, even when spikes...Full Text Available

Optimization of inspection and replacement period by using Bayesian statistics

There is no gold standard diagnostic test for the detection of bovine cryptosporidiosis. Infection is usually highest in 2-week-old calves, and these calves also excrete high numbers of oocysts. These...Full Text Available

2011-01-01

A Bayesian hierarchical approach to dual response surface modelling

This study describes the formulations to optimize the time interval of inspections and/or replacements of equipment/parts taking into account the probability density functions (PDF) for failure rates and parameters of failure distribution functions (FDF) and evaluates the optimized results of these time intervals using our formulations by comparing with those using only representative values of failure rates and the parameters of FDF instead of using these PDFs. The PDFs are obtained with Bayesian method and the representative values are obtained with likelihood estimation method. However, any significant difference is not observed between both optimized results within our preliminary calculations. (author)

2006-07-01

British Library Electronic Table of Contents (United Kingdom)

In modern quality engineering, dual response surface methodology is a powerful tool to model an industrial process by using both the mean and the standard deviation of the measurements as the responses. The least squares method in regression is often used to estimate the coefficients in the mean and standard deviation models, and various decision criteria are proposed by researchers to find the optimal conditions. Based on the inherent hierarchical structure of the dual response problems, we propose a Bayesian hierarchical approach to model dual response surfaces. Such an approach is compared with two frequentist least squares methods by using two real data sets and simulated data.

2011-01-01

Forecasting neutrino masses from combining KATRIN and the CMB: Frequentist and Bayesian analyses

Analysis of non-Gaussian CMB maps based on the N-pdf. Application to WMAP data

We present a showcase for deriving bounds on the neutrino masses from laboratory experiments and cosmological observations. We compare the frequentist and Bayesian bounds on the effective electron neutrino mass m_beta which the KATRIN neutrino mass experiment is expected to obtain, using both an analytical likelihood function and Monte Carlo simulations of KATRIN. Assuming a uniform prior in m_beta, we find that a null result yields an upper bound of about 0.17 eV at 90% confidence in the Bayesian analysis, to be compared with the frequentist KATRIN reference value of 0.20 eV. This is a significant difference when judged relative to the systematic and statistical uncertainties of the experiment. On the other hand, an input m_beta=0.35 eV, which is the KATRIN 5sigma detection threshold, would be detected at virtually the same level. Finally, we combine the simulated KATRIN results with cosmological data in the form of present (post-WMAP) and ...

2007-01-01

An Integrated Hydrologic Bayesian Multi-Model Combination Framework: Confronting Input, parameter and model structural uncertainty in Hydrologic Prediction

We present a new method based on the N-point probability distribution (pdf) to study non-Gaussianity in cosmic microwave background (CMB) maps. Likelihood and Bayesian estimation are applied to a local non-linear perturbed model up to third order, characterized by a linear term which is described by a Gaussian N-pdf, and a second and third order terms which are proportional to the square and the cube of the linear one. We also explore a set of model selection techniques (the Akaike and the Bayesian Information Criteria, the minimum description length, the Bayesian Evidence and the Generalized Likelihood Ratio Test) and their application to decide whether a given data set is better described by the proposed local non-Gaussian model, rather than by the standard Gaussian temperature distribution. As an application, we consider the analysis of the WMAP 5-year data at a resolution of around 2 degrees. At this angular scale (the ...

2008-01-01

1 2 3

QTL mapping in outbred half-sib families using Bayesian model selection.

This paper presents a new technique--Integrated Bayesian Uncertainty Estimator (IBUNE) to account for the major uncertainties of hydrologic rainfall-runoff predictions explicitly. The uncertainties from the input (forcing) data--mainly the precipitation observations and from the model parameters are reduced through a Monte Carlo Markov Chain (MCMC) scheme named Shuffled Complex Evolution Metropolis (SCEM) algorithm which has been extended to include a precipitation error model. Afterwards, the Bayesian Model Averaging (BMA) scheme is employed to further improve the prediction skill and uncertainty estimation using multiple model output. A series of case studies using three rainfall-runoff models to predict the streamflow in the Leaf River basin, Mississippi are used to examine the necessity and usefulness of this technique. The results suggests that ignoring either input forcings error or model structural uncertainty will lead to unrealistic ...

2006-05-05

Molecular phylogenetic relationships and phenotypic diversity in miniaturized toadlets, genus Brachycephalus (Amphibia: Anura: Brachycephalidae)

In this article, we propose a model selection method, the Bayesian composite model space approach, to map quantitative trait loci (QTL) in a half-sib population for continuous and binary traits. In our method, the identity-by-descent-based variance component model is used. To demonstrate the performance of this model, the method was applied to map QTL underlying production traits on BTA6 in a Chinese half-sib dairy cattle population. A total of four QTLs were detected, whereas only one QTL was identified using the traditional least square (LS) method. We also conducted two simulation experiments to validate the efficiency of our method. The results suggest that the proposed method based on a multiple-QTL model is efficient in mapping multiple QTL for an outbred half-sib population and is more powerful than the LS method based on a single-QTL model. PMID:21487433

2011-04-13

British Library Electronic Table of Contents (United Kingdom)

Toadlets of the genus Brachycephalus are endemic to the Atlantic rainforests of southeastern and southern Brazil. The 14 species currently described have snout-vent lengths less than 18mm and are thought to have evolved through miniaturization: an evolutionary process leading to an extremely small adult body size. Here, we present the first comprehensive phylogenetic analysis for Brachycephalus, using a multilocus approach based on two nuclear (Rag-1 and Tyr) and three mitochondrial (Cyt b, 12S, and 16S rRNA) gene regions. Phylogenetic relationships were inferred using a partitioned Bayesian analysis of concatenated sequences and the hierarchical Bayesian method (BEST) that estimates species trees based on the multispecies coalescent model. Individual gene trees showed conflict and also va...

2011-01-01

Gravity Dual for a Model of Perception

A Bayesian approach to analyze energy balance data from lactating dairy cows

One of the salient features of human perception is its invariance under dilatation in addition to the Euclidean group, but its non-invariance under special conformal transformation. We investigate a holographic approach to the information processing in image discrimination with this feature. We claim that a strongly coupled analogue of the statistical model proposed by Bialek and Zee can be holographically realized in scale invariant but non-conformal Euclidean geometries. We identify the Bayesian probability distribution of our generalized Bialek-Zee model with the GKPW partition function of the dual gravitational system. We provide a concrete example of the geometric configuration based on a vector condensation model coupled with the Euclidean Einstein-Hilbert action. From the proposed geometry, we study sample correlation functions to compute the Bayesian probability distribution.

2010-01-01

British Library Electronic Table of Contents (United Kingdom)

The objective of the present investigation was to develop a Bayesian framework for updating and integrating covariate information into key parameters of metabolizable energy (ME) systems for dairy cows. The study addressed specifically the effects of genetic improvements and feed quality on key parameters in current ME systems. These are net and metabolizable energy for maintenance (NEM and MEM, respectively), efficiency of utilization of ME for milk production (kL) and growth (kG), and efficiency of utilization of body stores for milk production (kT). Data were collated from 38 studies, yielding 701 individual cow observations on milk energy, ME intake, and tissue gain and loss. A function based on a linear relationship between milk energy and ME intake and correcting for tissue energy lo...

2011-01-01

A Bayesian Bioeconometric Model of Invasive Species Control: The Case of the Hemlock Woolly Adelgid

British Library Electronic Table of Contents (United Kingdom)

In this article we evaluate a US Forest Service plan to mitigate damages from an invasive insect on public, forested land. We develop a dynamic model of infestation and control to explicitly account for biological interactions, baseline conditions, and uncertainty, thus creating a more complete picture of policy impacts than a static cost benefit analysis could provide. We combine the results of the dynamic model with an empirical study of nonmarket forest benefits to create a bioeconomic model of ecosystem management. Estimating the empirical model in a Bayesian framework allows us to treat the economic coefficients of the dynamic model as random variables. We specify distributions for the biological parameters and examine the effects of both biological and economic uncertainty on the pre...

2011-01-01

The Bayesian analysis of zero-failure data for electrical products life testing

Long-run determinants of pollution: A robustness analysis

Power system components, especially components failure, can significantly affect the reliability of a power system. Data about failure rate in electrical products were obtained from products life testing and analyzed in order to predict reliability. The distribution curve fitting method was used to estimate failure probability. Ten relays of different life times have been used to illustrate the validity of this analytical technique. 3 refs., 3 tabs.

1997-12-31

British Library Electronic Table of Contents (United Kingdom)

This paper examines how robust economic, political, and demographic variables are related to water and air pollution. Employing Bayesian Averaging of Classical Estimates (BACE) for a cross section of 47 countries, 34 variables and 3 proxies for air and water pollution over a period from 1980 to 2000 we confirm the environmental Kuznets curve hypothesis and highlight the relevance of variables that are not directly related to production.

2009-01-01

Analytical peak fitting for gamma-ray spectrum analysis with Ge detectors

Analytical peak fitting for gamma-ray spectrum analysis with Ge detectors

A comparison of maximum likelihood (or chi-square) and Bayesian peak fitting techniques shows that the latter can reduce peak intensity uncertainties by a factor of up to ten in the case of closely separated doublets, leading to greatly improved doublet resolution. The need for laboratories to demonstrate the reliability of their chosen peak fitting techniques and measures of peak intensity is also demonstrated. (orig.)

1993-10-01

Comparative cold resistance of three Columbia River organisms

Off-grid Direction of Arrival Estimation Using Sparse Bayesian Inference

Resistance to abrupt and gradual cold shock was determined in bioassays with pumpkinseed (Lepomis gibbosus), rainbow trout (Salmo gairdneri), and a northwestern crayfish (Pacifastacus leniusculus) acclimated to higher temperatures at 5 C increments. Test criteria were median tolerance limits (TLm) for 96-h exposures after abrupt cold shock, and 50 percent loss of equilibrium (LE50) for decline rates of 18, 15, 10, 5, and 1 C/h during gradual cold shock. Cold resistance depended on original acclimation temperature (AT) and varied among species under both test conditions in the order: pumpkinseed less than rainbow trout less than crayfish. The lower TLm limit for pumpkinseed was 12.3 C at 30 C AT, 9.6 C at 25 C AT, 4.5 C at 20 C AT, and 2.7 C at 15 C AT. Rainbow trout at 20, 15 and 10 C AT survived abrupt exposures to cold down to 3.3, 1.4 and 0.5 C, respectively. Crayfish at 25, 20 and 15 C AT survived exposures down to 2.5, 0.4 and 0.0 C, respectively. TLm values ...

1977-03-01

Dynamic Batch Bayesian Optimization

This paper is focused on solving the narrowband direction of arrival estimation problem from a sparse signal reconstruction perspective. Existing sparsity-based methods have shown advantages over conventional ones but exhibit limitations in practical situations where the true directions are not in the sampling grid. A so-called off-grid model is broached to reduce the modeling error caused by the off-grid directions. An iterative algorithm is proposed in this paper to solve the resulting problem from a Bayesian perspective while joint sparsity among different snapshots is exploited by assuming the same Laplace prior. Like existing sparsity-based methods, the new approach applies to arbitrary sensor array and exhibits increased resolution and improved robustness to noise and source correlation. Moreover, our approach results in more accurate direction of arrival estimation, e.g., smaller bias and lower mean squared error. High precision can be obtained with a coarse ...

2011-01-01

Bayesian Based Comment Spam Defending Tool

Bayesian optimization (BO) algorithms try to optimize an unknown function that is expensive to evaluate using minimum number of evaluations/experiments. Most of the proposed algorithms in BO are sequential, where only one experiment is selected at each iteration. This method can be time inefficient when each experiment takes a long time and more than one experiment can be ran concurrently. On the other hand, requesting a fix-sized batch of experiments at each iteration causes performance inefficiency in BO compared to the sequential policies. In this paper, we present an algorithm that asks a batch of experiments at each time step t where the batch size p_t is dynamically determined in each step. Our algorithm is based on the observation that the sequence of experiments selected by the sequential policy can sometimes be almost independent from each other. Our algorithm identifies such scenarios and request those experiments at the same time without degrading the ...

2011-01-01

An adaptive filter to approximate the Bayesian strategy for sonographic beamforming.

Spam messes up user's inbox, consumes network resources and spread worms and viruses. Spam is flooding of unsolicited, unwanted e mail. Spam in blogs is called blog spam or comment spam.It is done by posting comments or flooding spams to the services such as blogs, forums,news,email archives and guestbooks. Blog spams generally appears on guestbooks or comment pages where spammers fill a comment box with spam words. In addition to wasting user's time with unwanted comments, spam also consumes a lot of bandwidth. In this paper, we propose a software tool to prevent such blog spams by using Bayesian Algorithm based technique. It is derived from Bayes' Theorem. It gives an output which has a probability that any comment is spam, given that it has certain words in it. With using our past entries and a comment entry, this value is obtained and compared with a threshold value to find if it exceeds the threshold value or not. By using this concept, we developed a software ...

2010-01-01

Cubature Kalman smoothers

A first-principles task-based approach to the design of medical ultrasonic imaging systems for breast lesion discrimination is described. This study explores a new approximation to the ideal Bayesian observer strategy that allows for object heterogeneity. The new method, called iterative Wiener filtering, is implemented using echo data simulations and a phantom study. We studied five lesion features closely associated with visual discrimination for clinical diagnosis. A series of human observer measurements for the same image data allowed us to quantitatively compare alternative beamforming strategies through measurements of visual discrimination efficiency. Employing the Smith-Wagner model observer, we were able to breakdown efficiency estimates and identify the processing stage at which performance losses occur. The methods were implemented using a commercial scanner and a cyst phantom to explore development of spatial filters for systems with shift-variant ...

2010-07-19

British Library Electronic Table of Contents (United Kingdom)

The cubature Kalman filter (CKF) is a relatively new addition to derivative-free approximate Bayesian filters built under the Gaussian assumption. This paper extends the CKF theory to address nonlinear smoothing problems; the resulting state estimator is named the fixed-interval cubature Kalman smoother (FI-CKS). Moreover, the FI-CKS is reformulated to propagate the square-root error covariances. Although algebraically equivalent to the FI-CKS, the square-root variant ensures reliable implementation when committed to embedded systems with fixed precision or when the inference problem itself is ill-conditioned. Finally, to validate the formulation, the square-root FI-CKS is applied to track a ballistic target on reentry.

2011-01-01

A Fast Audio Clustering Using Vector Quantization and Second Order Statistics

Phylogeny of iguanian lizards inferred from 29 nuclear loci, and a comparison of concatenated and species-tree approaches for an ancient, rapid radiation.

This paper describes an effective unsupervised speaker indexing approach. We suggest a two stage algorithm to speed-up the state-of-the-art algorithm based on the Bayesian Information Criterion (BIC). In the first stage of the merging process a computationally cheap method based on the vector quantization (VQ) is used. Then in the second stage a more computational expensive technique based on the BIC is applied. In the speaker indexing task a turning parameter or a threshold is used. We suggest an on-line procedure to define the value of a turning parameter without using development data. The results are evaluated using 10 hours of audio data.

2010-01-01

The estimation of lifetime distribution of Alloy 800 steam generator tubing

Iguanian lizards form a diverse clade whose members have been the focus of many comparative studies of ecology, behavior, and evolution. Despite the importance of phylogeny to such studies, interrelationships among many iguanian clades remain uncertain. Within the Old World clade Acrodonta, Agamidae is sometimes found to be paraphyletic with respect to Chamaeleonidae, and recent molecular studies have produced conflicting results for many major clades. Within the largely New World clade Pleurodonta, relationships among the 12 currently recognized major subclades (mostly ranked as families) have been largely unresolved or poorly supported in previous studies. To clarify iguanian evolutionary history, we first infer phylogenies using concatenated maximum-likelihood (ML) and Bayesian analyses of DNA sequence data from 29 nuclear protein-coding genes for 47 iguanian and 29 outgroup taxa. We then estimate a relaxed-clock Bayesian chronogram for ...

2011-07-20

The estimation of lifetime distribution of Alloy 800 steam generator tubing

Alloy 800 has been used for steam generator (SG) tubing for more than 30 years, primarily in CANDU reactors worldwide and in reactors in Germany. Extensive laboratory testing and in-service experience suggest that the Alloy 800 tubing has excellent resistance to corrosion-related degradation under appropriate operating conditions. In planning refurbishment of nuclear plants stations, a key concern is the longevity of existing SGs up to the 60-year lifetime of the refurbished plant. The paper reviews an existing methodology based on the concept of the improvement factor, and refines its estimation based on data specific to CANDU operating conditions. The paper presents a more advanced Bayesian probabilistic approach to estimate the degradation free lifetime distribution of Alloy 800 tubing, which is used to quantify the probability of degradation during the service life and to evaluate the impact of potential occurrences of degradation on reliability of SG tubing.

2009-10-15

Road Interpretation for Driver Assistance Based on an Early Cognitive Vision System

2009-10-01

1 2 3

DEFF Research Database (Denmark)

In this work, we address the problem of road interpretation for driver assistance based on an early cognitive vision system. The structure of a road and the relevant traf?c are interpreted in terms of ego-motion estimation of the car, independently moving objects on the road, lane markers and large scale maps of the road. We make use of temporal and spatial disambiguation mechanisms to increase the reliability of visually extracted 2D and 3D information. This information is then used to interpret the layout of the road by using lane markers that are detected via Bayesian reasoning. We also estimate the ego-motion of the car which is used to create large scale maps of the road and also to detect independently moving objects. Sample results for the presented algorithms are shown on a stereo image sequence, that has been collected from a structured road.

2009-01-01

Reliability data update method for emergency diesel generator of Daya Bay Nuclear Power Plant

British Library Electronic Table of Contents (United Kingdom)

In the field of Living Probabilistic Safety Assessment (LPSA) the reliability data updating is an important factor. In risk analysis equipment failure data is needed to estimate the frequencies of events contributing to risk posed by a facility. Five years data of emergency diesel generator (EDG) of Daya Bay Nuclear Power Plant (NPP) has been studied in this paper. The data updating process has been done by using two methods, i.e., the classical method and Bayesian method. The aim of using these methods is to calculate the operational failure rate (@l) and demand failure probability (p). The results show that the operational failure rate is 1.7E-3 per hour and the demand failure probability is 2.4E-2 demand per day for Daya Bay NPP. By comparing the results obtain from classical and Bayesi...

2011-01-01

Phylogeography of rabies virus isolated from dogs in Brazil between 1985 and 2006

British Library Electronic Table of Contents (United Kingdom)

To establish the phylogeographic relationships in rabies viruses in Brazil, we studied a dataset retrieved from GenBank consisting of 71 genetic sequences from the coding region of the N gene of rabies viruses isolated in dogs over a period of 22?years. The Bayesian Markov chain Monte Carlo method available in the BEAST package was used with the GTR+G+?4 evolutionary model in conjunction with the relaxed uncorrelated lognormal molecular clock model and an exponential growth tree prior. A discrete phylogeographic diffusion model was also analyzed using a standard continuous-time Markov chain viewed with Google Earth to provide a spatial projection of the diffusion of genetic lineages based on their phylogeographic relationships. The topology of the time and substitution phylogenetic trees a...

2011-01-01

Bayesian synthesis of epidemiological evidence with different combinations of exposure groups: application to a gene-gene-environment interaction

British Library Electronic Table of Contents (United Kingdom)

Meta-analysis to investigate the joint effect of multiple factors in the aetiology of a disease is of increasing importance in epidemiology. This task is often challenging in practice, because studies typically concentrate on studying the effect of only one exposure, sometimes may report the interaction between two exposures, but rarely address more complex interactions that involve more than two exposures. In this paper, we develop a meta-analysis framework that combines estimates from studies of multiple exposures. A key development is an approach to combining results from studies that report information on any subset or combination of the full set of exposures.The model requires assumptions to be made about the prevalence of the specific exposures. We discuss several possible model spec...

2006-01-01

A new formulation of asset trading games in continuous time with essential forcing of variation exponent

A methodology to model causal relationships on offshore safety assessment focusing on human and organizational factors

We introduce a new formulation of asset trading games in continuous time in the framework of the game-theoretic probability established by Shafer and Vovk (2001). In our formulation, the market moves continuously but an investor trades in discrete times, which can depend on the past path of the market. We prove that an investor can essentially force that the asset price path behaves with the variation exponent exactly equal to two. Our proof is based on embedding high-frequency discrete time games into the continuous time game and the use of the Bayesian strategy of Kumon, Takemura and Takeuchi (2007b) for discrete time coin-tossing games. We also clarify that the main growth part of the investor's capital processes is lucidly described by the information quantities, which are derived from the Kullback-Leibler information with respect to the empirical fluctuation of the asset price.

2007-01-01

British Library Electronic Table of Contents (United Kingdom)

IntroductionFocusing on people and organizations, this paper aims to contribute to offshore safety assessment by proposing a methodology to model causal relationships.MethodThe methodology is proposed in a general sense that it will be capable of accommodating modeling of multiple risk factors considered in offshore operations and will have the ability to deal with different types of data that may come from different resources. Reason's ?Swiss cheese?? model is used to form a generic offshore safety assessment framework, and Bayesian Network (BN) is tailored to fit into the framework to construct a causal relationship model. The proposed framework uses a five-level-structure model to address latent failures within the causal sequence of events. The five levels include Root causes level, Tr...

2008-01-01

Wiener Reconstruction of Large-Scale Structure from Peculiar Velocities

Study of core collapse neutrino signals and constraints on neutrino masses from a future Galactic Supernova

We present an alternative, Bayesian method for large-scale reconstruction from observed peculiar velocity data. The method stresses a rigorous treatment of the random errors and it allows extrapolation into poorly sampled regions in real space or in k-space. A likelihood analysis is used to determine the fluctuation power spectrum, followed by a Wiener Filter (WF) analysis to obtain the minimum-variance mean fields of velocity and mass density. Constrained Realizations (CR) are then used to sample the statistical scatter about the WF mean field. The WF/CR method is applied as a demonstration to the Mark III data with 1200 km/s, 900 km/s, and 500 km/s resolutions. The main reconstructed structures are consistent with those extracted by the POTENT method. A comparison with the structures in the distribution of IRAS 1.2Jy galaxies yields a general agreement. The reconstructed velocity field is decomposed into its divergent and tidal components relative to a cube of ...

1999-01-01

Stochastic Inversion of Electrical Resistivity Changes Using a Markov Chain, Monte Carlo Approach

We study the sensitivity to neutrino masses of a Galactic supernova neutrino signal as could be measured with the detectors presently in operation and with future large volume water \\v{C}erencov and scintillator detectors. The analysis uses the full statistics of neutrino events. The method proposed uses the principles of Bayesian inference reasoning and has shown a remarkably independence of astrophysical assumptions. We show that, after accounting for the uncertainties in the detailed astrophysical description of the neutrino signal and taking into account the effects of neutrino oscillations in the supernova mantle, detectors presently in operation can have enough sensitivity to reveal a neutrino mass (or to set upper limits) at the level of 1 eV. This is sensibly better than present results from tritium $\\beta$-decay experiments, competitive with the most conservative limits from neutrinoless double $\\beta$-decay and less precise but remarkably less ...

2005-01-01

Molecular phylogenetic analysis of tropical freshwater mussels (Mollusca: Bivalvia: Unionoida) resolves the position of Coelatura and supports a monophyletic Unionidae.

We describe a stochastic inversion method for mapping subsurface regions where the electrical resistivity is changing. The technique combines prior information, electrical resistance data and forward models to produce subsurface resistivity models that are most consistent with all available data. Bayesian inference and a Metropolis simulation algorithm form the basis for this approach. Attractive features include its ability to: (1) provide quantitative measures of the uncertainty of a generated estimate and, (2) allow alternative model estimates to be identified, compared and ranked. Methods that monitor convergence and summarize important trends of the posterior distribution are introduced. Results from a physical model test and a field experiment were used to assess performance. The stochastic inversions presented provide useful estimates of the most probable location, shape, and volume of the changing region, and the most likely resistivity change. The proposed ...

2004-09-21

Incorporating organizational factors into Probabilistic Risk Assessment (PRA) of complex socio-technical systems: A hybrid technique formalization

In previous molecular phylogenetic analyses of the freshwater mussel family Unionidae (Bivalvia: Unionoida), the Afrotropical genus Coelatura had been recovered in various positions, generally indicating a paraphyletic Unionidae. However that result was typically poorly supported and in conflict with morphology-based analyses. We set out to test the phylogenetic position of Coelatura by sampling tropical lineages omitted from previous studies. Forty-one partial 28S nuclear rDNA and partial COI mtDNA sequences (1130 total aligned nucleotides) were analyzed separately and in combination under both maximum parsimony and likelihood, as well as Bayesian inference. There was significant phylogenetic incongruence between the character sets (partition homogeneity test, p<0.01), but a novel heuristic for comparing bootstrap values among character sets analyzed separately and in combination illustrated that the observed conflict was due to homoplasy rather than separate ...

2011-07-30

Dimensionless energy confinement scaling in W7-AS

This paper is a result of a research with the primary purpose of extending Probabilistic Risk Assessment (PRA) modeling frameworks to include the effects of organizational factors as the deeper, more fundamental causes of accidents and incidents. There have been significant improvements in the sophistication of quantitative methods of safety and risk assessment, but the progress on techniques most suitable for organizational safety risk frameworks has been limited. The focus of this paper is on the choice of 'representational schemes' and 'techniques.' A methodology for selecting appropriate candidate techniques and their integration in the form of a 'hybrid' approach is proposed. Then an example is given through an integration of System Dynamics (SD), Bayesian Belief Network (BBN), Event Sequence Diagram (ESD), and Fault Tree (FT) in order to demonstrate the feasibility and value of hybrid techniques. The ...

2009-05-15

Development of pile foundation bias factors using observed behavior of platforms during Hurricane Andrew

Energy confinement in W7-AS has been analyzed in terms of dimensionally exact form free functions employing Bayesian probability theory. The confinement function was set up as a linear combination of dimensionally exact power law terms as already proposed very early by Connor and Taylor. Generation of this expansion basis is dictated by the basic plasma model which one assumes. Based upon data accumulated in W7-AS, which contains the energy content for a wide variety of variable settings, predictions for single variable scans are made. The scaling functions for density and power scans, respectively, are in quantitative agreement with data collected in W7-AS. The result of a single variable scan is therefore already hidden in the data obtained for arbitrary variable choices and can be extracted from the latter by a proper data analysis. Furthermore, the optimal model for the description of the global transport in W7-AS is identified as the collisional low beta ...

1999-12-01

Contributions to the Analysis of Spatial and Spatial-Temporal Data

The performance of more than 3,000 offshore platforms in the Gulf of Mexico was observed during the passage of Hurricane Andrew in August 1992. This event provided an opportunity to test the procedures used for platform analysis and design. A global bias was inferred for overall platform capacity and loads in the Andrew Joint Industry Project (JIP) Phase 1. It was predicted that the pile foundations of several platforms should have failed, but did not. These results indicated that the biases specific to foundation failure modes may be higher than those of jacket failure modes. The biases in predictions of foundation failure modes were therefore investigated further in this study. The work included capacity analysis and calibration of predictions with the observed behavior for 3 jacket platforms and 3 caissons using Bayesian updating. Bias factors for two foundation failure modes, lateral shear and overturning, were determined for each structure. Foundation capacity ...

1996-12-31

A sensitive submillimetre survey of Broad Absorption Line quasars

This doctoral thesis addresses some problems in the analysis of spatial and spatial-temporal data and discusses prediction, prediction errors and identification of emission sources. European sulphur data are used as illustration. In an investigation of a spatial-temporal decomposition model for improving estimates of spatial interpolation (prediction) errors from monitoring data, the estimates were improved compared to estimates obtained by the method known as Kriging (an extension of the Wiener-Kolmogorov theory from time series to spatial processes), although the interpolated values were quite similar. A study of a random process model with an unknown, slowly varying trend and a correlated residual process is performed, using both trend estimation (smoothing) and prediction. Local polynomial methods are extended to continuous random processes. A new approach to non-parametric smoothing and to non-parametric Kriging is described. Finally, a statistical method for verifying reported ...

1996-12-31

Neutron Resonance Parameters of 55Mn from Reich-Moore Analysis of Recent Experimental Neutron Transmission and Capture Cross Sections

Using the SCUBA bolometer array on the JCMT, we have carried out a submillimetre survey of Broad Absorption Line quasars (BALQs). The sample has been chosen to match, in redshift and optical luminosity, an existing benchmark 850um sample of radio-quiet quasars, allowing a direct comparison of the submm properties of BAL quasars relative to the parent radio-quiet population. We reach a submm limit 1.5mJy at 850um, allowing a more rigorous measure of the submm properties of BAL quasars than previous studies. Our submm photometry complements extensive observations at other wavelengths, in particular X-rays with Chandra and mid-infrared with Spitzer. To compare the 850um flux distribution of BALQs with that of the non-BAL quasar benchmark sample, we employ a suite of statistical methods, including survival analysis and a novel Bayesian derivation of the underlying flux distribution. Although there are no strong grounds for rejecting the null hypothesis that BALQs on ...

2006-01-01

Grid-Search Location Methods for Ground-Truth Collection From Local and Regional Seismic Networks

High-resolution neutron capture cross section measurements of 55Mn were recently performed at GELINA by Schillebeeckx et al. (2005) and at ORELA by Guber et al. (2007). The analysis of the experimental data was performed with the computer code SAMMY using the Bayesian approach in the resonance parameters representation of the cross sections. The neutron transmission data taken in 1988 by Harvey et al. (2007) and not analyzed before were added to the SAMMY experimental data base. More than 95% of the s-wave resonances and more than 85% of the p-wave resonances were identified in the energy range up to 125 keV, leading to the neutron strength functions S0 = (3.90 0.78) x 10-4 and S1 = (0.45 0.08) x 10-4. About 25% of the d-wave resonances were identified with a possible strength function of S2 = 1.0 x 10-4. The capture cross section calculated at 0.0253 eV is 13.27 b, and the capture resonance integral is 13.52 0.30 b. In the energy range 15 to 120 keV, the average ...

2008-05-01

Combining rock physics and sedimentology for seismic reservoir characterization of North Sea turbidite systems

This project investigated new techniques for improving seismic event locations derived from regional and local networks. The technqiues include a new approach to empirical travel-time calibration that simultaneously fits data from multiple stations and events, using a generalization of the kriging method, and predicts travel-time corrections for arbitrary event-station paths. We combined this calibration approach with grid-search event location to produce a prototype new multiple-event location method that allows the use of spatially well-distributed events and takes into account correlations between the travel-time corrections from proximate event-station paths. Preliminary tests with a high quality data set from Nevada Test Site explosions indicated that our new calibration/location method offers improvement over the conventional multiple-event location methods now in common use, and is applicable to more general event-station geometries than the conventional methods. The tests were ...

2005-05-13

Combined Estimation of Hydrogeologic Conceptual Model, Parameter, and Scenario Uncertainty with Application to Uranium Transport at the Hanford Site 300 Area

The petroleum industry is increasing its focus on the exploration of reservoirs in turbidite systems. However, these sedimentary environments are often characterized by very complex sand distributions. Hence, reservoir description based on conventional seismic and well-log interpretation may be very uncertain. There is a need to employ more quantitative seismic techniques to reveal reservoirs units in these complex systems from seismic amplitude data. In this study we focus on North Sea turbidite systems. Our goal is to improve the ability to use 3D seismic data to map reservoirs in these systems. A cross-disciplinary methodology for seismic reservoir characterization is presented that combines rock physics, sedimentology, and statistical techniques. We apply this methodology to two turbidite systems of Paleocene age located in the South Viking Graben of the North Sea. First, we investigate the relationship between sedimentary petrography and rock physics properties. Next, we define ...

2000-01-01

Pixel-based and object-oriented change detection analysis using high-resolution imagery

This report to the Nuclear Regulatory Commission (NRC) describes the development and application of a methodology to systematically and quantitatively assess predictive uncertainty in groundwater flow and transport modeling that considers the combined impact of hydrogeologic uncertainties associated with the conceptual-mathematical basis of a model, model parameters, and the scenario to which the model is applied. The methodology is based on a n extension of a Maximum Likelihood implementation of Bayesian Model Averaging. Model uncertainty is represented by postulating a discrete set of alternative conceptual models for a site with associated prior model probabilities that reflect a belief about the relative plausibility of each model based on its apparent consistency with available knowledge and data. Posterior model probabilities are computed and parameter uncertainty is estimated by calibrating each model to observed system behavior; prior parameter estimates ...

2007-07-30