summary.postpr: Posterior model probabilities and Bayes factors

Description Usage Arguments Value See Also Examples

View source: R/postpr.R

Description

This function extracts the posterior model probabilities and calculates the Bayes factors from an object of class "postpr".

Usage

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## S3 method for class 'postpr'
summary(object, rejection = TRUE, print = TRUE, digits
= max(3, getOption("digits")-3), ...)

Arguments

object

an object of class "postpr".

rejection

logical, if method is "mnlogistic" or "neuralnet", should the approximate model probabilities based on the rejection method returned.

print

logical, if TRUE prints the mean models probabilities.

digits

the digits to be rounded to.

...

other arguments.

Value

A list with the following components if method="rejection":

Prob

an object of class table of the posterior model probabilities.

BayesF

an object of class table with the Bayes factors between pairs of models.

A list with the following components if method is "mnlogistic" or "neuralnet" and rejection is TRUE:

rejection

a list with the same components as above

mnlogistic

a list with the same components as above

See Also

postpr

Examples

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## see ?postpr for examples

abc documentation built on May 20, 2017, 4:40 a.m.

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