Model Selection with Bayesian Methods and Information Criteria
Priors on model space for variable selection problems
Model with best AIC, BIC, EBIC or other general information criteria (...
Number of Normal mixture components under Normal-IW and Non-local prio...
Treatment effect estimation for linear models via Confounder Importanc...
Density and random draws from the asymmetric Laplace distribution
Dirichlet density
Density for Inverse Wishart distribution
Non-local prior density, cdf and quantile functions.
Posterior Normal-IWishart density
Expectation of a product of powers of Normal or T random variables
Obtain AIC, BIC, EBIC or other general information criteria (getIC)
Class "icfit"
Extract estimated inverse covariance
Local variable selection
Marginal likelihood under a multivariate Normal likelihood and a conju...
Class "mixturebf"
Moment and inverse moment prior elicitation
Bayesian variable selection for linear models via non-local priors.
Bayesian variable selection for linear models via non-local priors.
Moment and inverse moment Bayes factors for linear models.
Bayes factors for moment and inverse moment priors
Class "msfit"
Class "msfit_ggm"
Class "msPriorSpec"
Marginal density of the observed data for linear regression with Norma...
Plot estimated marginal prior inclusion probabilities
Bayesian model selection and averaging under block-diagonal X'X for li...
Obtain posterior model probabilities
Extract posterior samples from an object
Posterior sampling for regression parameters
Model selection and averaging for regression and mixtures, inclusing Bayesian model selection and information criteria (BIC, EBIC, AIC, GIC).