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summary.postpr

Posterior model probabilities and Bayes factors

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

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

`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.

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 ?postpr for examples

Tools for Approximate Bayesian Computation (ABC)

v2.1

GPL (>= 3)

Authors

Csillery Katalin [aut], Lemaire Louisiane [aut], Francois Olivier [aut], Blum Michael [aut, cre]

Initial release

2015-05-04