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abc (version 2.0)

summary.postpr: Posterior model probabilities and Bayes factors

Description

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

Usage

## 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":
  • Proban object of class table of the posterior model probabilities.
  • BayesFan 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:
  • rejectiona list with the same components as above
  • mnlogistica list with the same components as above

See Also

postpr

Examples

Run this code
## see ?postpr for examples

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