Obtain posterior model probabilities after running Bayesian model selection
postProb(object, nmax, method='norm')A data.frame with posterior model probabilities in column pp.
Column modelid indicates the indexes of the selected covariates (empty
for the null model with no covariates)
For mixturebf objects, posterior probabilities for the
specified number of components
For localtest objects, posterior probabilities of a local covariate
effect at various regions
Object of class msfit returned by modelSelection,
class mixturebf returned by bfnormmix,
class cilfit returned by cil
or class localtest returned by localnulltest
Maximum number of models to report (defaults to no max)
Only when class(object) is msfit.
For 'norm' probabilities are obtained by renormalizing the
stored integrated likelihoods, for 'exact' they are given by the proportion
of MCMC visits to each model. 'norm' has less variability but can be biased
if the chain has not converged.
David Rossell
modelSelection to perform model selection