Priors on model space for variable selection problems

Share:

Description

unifPrior implements a uniform prior (equal a priori probability for all models). binomPrior implements a Binomial prior. bbPrior implements a Beta-Binomial prior.

Usage

1
2
3
unifPrior(sel, logscale = TRUE)
binomPrior(sel, prob = 0.5, logscale = TRUE)
bbPrior(sel, alpha = 1, beta = 1, logscale = TRUE) 

Arguments

sel

Logical vector indicating which variables are included in the model

logscale

Set to TRUE to return the log-prior probability.

prob

Success probability for the Binomial prior

alpha

First parameter of the Beta-Binomial prior, which is equivalent to specifying a Beta(alpha,beta) prior on prob.

beta

First parameter of the Beta-Binomial prior, which is equivalent to specifying a Beta(alpha,beta) prior on prob.

Value

Prior probability of the specified model

Author(s)

David Rossell

Examples

1
2
3
4
5
library(mombf)
sel <- c(TRUE,TRUE,FALSE,FALSE)
unifPrior(sel,logscale=FALSE)
binomPrior(sel,prob=.5,logscale=FALSE)
bbPrior(sel,alpha=1,beta=1,logscale=FALSE)