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Criteria for Bayesian model choice with application to variable selection
Model selection variable selection objective Bayes.
2012/11/23
In objective Bayesian model selection, no single criterion has emerged as dominant in defining objective prior distributions. Indeed, many criteria have been separately proposed and utilized to propos...
Criteria for Bayesian model choice with application to variable selection
Model selection variable selection objective Bayes.
2012/11/23
In objective Bayesian model selection, no single criterion has emerged as dominant in defining objective prior distributions. Indeed, many criteria have been separately proposed and utilized to propos...
spikeSlabGAM: Bayesian Variable Selection, Model Choice and Regularization for Generalized Additive Mixed Models in R
MCMC P-splines spike-and-slab prior normal-inverse-gamma
2011/6/20
The R package spikeSlabGAM implements Bayesian variable selection, model choice,
and regularized estimation in (geo-)additive mixed models for Gaussian, binomial, and
Poisson responses. Its purpose ...
Lack of confidence in ABC model choice
Lack of confidence ABC model choice Approximate Bayesian computation
2011/3/24
Approximate Bayesian computation (ABC) have become a essential tool for the analysis of complex stochastic models. Earlier, Grelaud et al. (2009) advocated the use of ABC for Bayesian model choice in ...
Bayesian inference and model choice in a hidden stochastic two-compartment model of hematopoietic stem cell fate decisions
Stochastic two-compartment model hidden Markov models reversible jump MCMC hematopoiesis stem cell asymmetric division
2010/11/8
Despite rapid advances in experimental cell biology, the in vivo behavior of hematopoietic stem cells (HSC) cannot be directly ob-served and measured. Previously we modeled feline hematopoiesis using ...
ABC likelihood-free methods for model choice in Gibbs random fields
Approximate Bayesian Computation model choice Gibbs Random Fields Bayes factor protein folding
2009/9/24
Gibbs random fields (GRF) are polymorphous statistical models that can be used to analyse different types of dependence, in particular for spatially correlated data. However, when tho...