postProb: Obtain posterior model probabilities

In mombf: Bayesian Model Selection and Averaging for Non-Local and Local Priors

Description

Obtain posterior model probabilities after running Bayesian model selection

Usage

  postProb(object, nmax, method='norm')

Arguments

object	Object of class msfit returned by modelSelection or class mixturebf, e.g. returned by bfnormmix
nmax	Maximum number of models to report (defaults to no max)
method	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.

Value

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).

Author(s)

David Rossell

See Also

modelSelection to perform model selection

Examples

#See help(modelSelection)

mombf documentation built on Dec. 6, 2019, 3:01 a.m.