Analysis using the Bayesian approach
Analysis of claim frequency and claim size using the Bayesian approach
... The analysis of claim frequency is based on the Bayesian approach and ...by using simulated samples to compute the posterior mean, standard deviation and percentiles for all ...
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Analysis of generalized nonlinear structural equation models by using Bayesian approach with application
... this analysis was to use multiple group NSEMs to obtain all the estimated parameters and to solve the problem of ordered categorical variables by using hidden continuous normal ...non-parametric ...
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A predictive Bayesian approach to risk analysis in health care
... frequency approach, reflecting the average state of a number of human and organisational ...risk analysis includes iden- tification of hazards and threats, cause analyses, consequence analyses and risk ...
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Analysis of COSIMA spectra: Bayesian approach
... of Bayesian analysis methods applied to time-of-flight secondary ion mass spectrometer (TOF-SIMS) ...the analysis can be broken into subgroups of lines close to integer mass ...other analysis ...
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eQuIPS: eQTL Analysis Using Informed Partitioning of SNPs – A Fully Bayesian Approach
... a Bayesian multi-SNP MCMC approach that allows published functional significance scores to objectively inform SNP prior effect sizes in eQTL ...analysed using the modified Normal Gamma increase ...
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eQuIPS: eQTL Analysis Using Informed Partitioning of SNPs – A Fully Bayesian Approach
... a Bayesian multi-SNP MCMC approach that allows published functional significance scores to objectively inform SNP prior effect sizes in eQTL ...analysed using the modified Normal Gamma increase ...
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Paired Comparison Analysis of the van Baaren Model Using Bayesian Approach with Noninformative Prior
... Keywords: Bayesian hypothesis testing, Noninformative priors, Posterior distribution, Predictive probability. 1. Introduction When the objects that can be scored on the same scale are compared, they are ranked on ...
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Bayesian approach to single-cell differential expression analysis
... All similarity measures do well when all 90+ cells and a complete gene set are considered. To provide a meaningful comparison we measured performance on more challenging classification problems based on partial data. ...
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STATISTICAL ANALYSIS OF THE TM- MODEL VIA BAYESIAN APPROACH
... In addition, the graphs of the marginal posterior distributions of the individual parameter are drawn. The appropriateness of the model is also tested using the different test-statistics. Keywords: Paired ...
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A marginalized variational bayesian approach to the analysis of array data
... Abstract Background: Bayesian unsupervised learning methods have many applications in the analysis of biological data. For example, for the cancer expression array datasets presented in this study, they can ...
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The Plausible and the Possible: A Bayesian Approach to the Analysis of Reasonable Suspicion
... So, in the context of a Terry stop, we can model reasonable suspicion as: (a) the likelihood of observing behaviors if criminal activity is afoot (the current Supreme Court[r] ...
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A Bayesian Approach for the Multifractal Analysis of Spatio-Temporal Data
... The Bayesian model is designed in such a way that the conditional distributions of the resulting joint posterior can be sampled without MHG ...associated Bayesian estimator by means of an MCMC algorithm is ...
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A Formal, Bayesian Approach for Uncertainty Analysis of a Watershed Model
... Efficient and robust sampling method is a prerequisite to successfully adopting Bayesian analysis. Yet, the reliability of the sampled posterior distribution, and corresponding estimates of parameter and ...
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Analysis of Blood Transfusion Data Using Bivariate Zero-Inflated Poisson Model: A Bayesian Approach
... analyzed using the Bayesian approach applying noninformative priors at the presence and absence of ...compared using the deviance information criteria ...
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Risk Informed Validation Framework Using Bayesian Approach.
... novel approach to quantitatively assess the system level validation by connecting individual validation events through a PRA informed validation ...a Bayesian network that allows propagation of fragility ...
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Bayesian Stochastic Frontier Analysis Using WinBUGS
... An improvement in fit may arise through careful selection of the higher order terms and interactions or of various other covariates. In the example above, we might wish to allow for the possibility of no time trend, a ...
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Bayesian survival analysis using gene expression
... the Bayesian Weibull model with MCMC compu- tational methods to predict patient ...of Bayesian survival models using gene expression levels as covariates was discussed and published procedures were ...
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Detection of Primary User in Cognitive Radio Using Bayesian Approach
... not using it ...detector, Bayesian detector and Approximate Bayesian detector for digitally modulated primary user to maximize the spectrum utilization, without prior information of transmitted ...
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Analysis of CT Liver Images Using Level Sets with Bayesian Analysis A Hybrid Approach
... tumor analysis because of its faster acquisition and compatibility with most life support ...image analysis. Active contour based tumor segmentation using classical level set methods easily suffer ...
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A Note on 'Bayesian analysis of the random coefficient model using aggregate data', an alternative approach
... estimation approach leads to accurate results, and the approach is shown to be capable of estimating the discussed model with a simpler estimation procedure and with less computational ...introduced ...
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