Results 31 to 40 of about 539,449 (277)
Post hoc Bayesian model selection
NeuroImage, 2011 This note describes a Bayesian model selection or optimization procedure for post hoc inferences about reduced versions of a full model. The scheme provides the evidence (marginal likelihood) for any reduced model as a function of the posterior density over the parameters of the full model.
Friston, Karl, Penny, Will
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Posterior Predictive Bayesian Phylogenetic Model Selection [PDF]
Systematic Biology, 2013 We present two distinctly different posterior predictive approaches to Bayesian phylogenetic model selection and illustrate these methods using examples from green algal protein-coding cpDNA sequences and flowering plant rDNA sequences. The Gelfand-Ghosh (GG) approach allows dissection of an overall measure of model fit into components due to posterior
Paul O, Lewis +4 more
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Bayesian Model Selection for Generalized Linear Mixed Models
Biometrics, 2023 AbstractWe propose a Bayesian model selection approach for generalized linear mixed models (GLMMs). We consider covariance structures for the random effects that are widely used in areas such as longitudinal studies, genome-wide association studies, and spatial statistics.
Shuangshuang Xu +3 more
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Test optimization selection method based on NSGA-3 and improved Bayesian network model
Xibei Gongye Daxue Xuebao, 2021 Most of the solutions to existing test selection problems are based on single-objective optimization algorithms and multi-signal models, which maybe lead to some problems such as rough index calculation and large solution set limitations.
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Bayesian Model Averaging, Learning, and Model Selection* [PDF]
, 2013 Agents have two forecasting models, one consistent with the unique rational expectations equilibrium, another that assumes a time-varying parameter structure. When agents use Bayesian updating to choose between models in a self-referential system, we find that learning dynamics lead to selection of one of the two models.
Evans, George W. +3 more
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PAC-Bayesian Stochastic Model Selection [PDF]
Machine Learning, 2003 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Bayesian model selection for LISA pathfinder [PDF]
Physical Review D, 2014 The main goal of the LISA Pathfinder (LPF) mission is to fully characterize the acceleration noise models and to test key technologies for future space-based gravitational-wave observatories similar to the eLISA concept. The data analysis team has developed complex three-dimensional models of the LISA Technology Package (LTP) experiment on-board LPF ...
Nikolaos Karnesis +14 more
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Bayesian Model Selection of Lithium-Ion Battery Models via Bayesian Quadrature
IFAC-PapersOnLine, 2023 11 pages, 2 figures, accepted at ...
Adachi, Masaki +5 more
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On model selection in cosmology
SciPost Physics Lecture Notes, 2019 We review some of the common methods for model selection: the goodness of fit, the likelihood ratio test, Bayesian model selection using Bayes factors, and the classical as well as the Bayesian information theoretic approaches.
Martin Kerscher, Jochen Weller
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Approximate Bayesian Model Selection with the Deviance Statistic [PDF]
, 2015 Bayesian model selection poses two main challenges: the specification of parameter priors for all models, and the computation of the resulting Bayes factors between models.
Bové, Daniel Sabanés +2 more
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