CalcBF: Calculates Bayes factors and posterior probabilities from the...

In rich-d-wilkinson/precision: Statistical methods for detecting non-binomial sex allocation when developmental mortality operates

Description

Calculates Bayes factors and posterior probabilities from the log model evidences.

Usage

CalcBF(log.evidence)

Arguments

log.evidence

A vector of length three containing the log.evidences for each of the three models. Should be ordered as c(binomial, multbinom, doublebinom)

Details

Given a vector of the logarithm of the model evidences, CalcBF calculates the Bayes factors for all three combinations, and the posterior probabilities assuming that each model is equally likely a priori.

Value

BF	Bayes factors
probH0	Posterior probability if the three models are equally likely a priori.

Author(s)

Richard Wilkinson

Examples

log.evidence<-c(-44, -38, -41)
CalcBF(log.evidence)

rich-d-wilkinson/precision documentation built on May 27, 2019, 7:41 a.m.