LOGIT (version 1.3)

jhbayes: Two functions to provide better JAGS model output

Description

For use with JAGS from within the R environment. Provides a nicer model output than comes with the default JAGS output.

Usage

#source("jhbayes.r")

Arguments

x

Variable arguments based on model

Details

Load jhbayes.r prior to running JAGS model. MyBUGSOutput and uNames functions will then be in memory. From Alain Zuur support files on highstat.com.

References

Hilbe, Joseph M. (2015), Practical Guide to Logistic Regression, Chapman & Hall/CRC, page 137-143.

Zuur, A.F., Hilbe, J.M., and Ieno, E.N. (2013), A Beginner's Guide to GLM and GLMM with R: a frequentist and Bayesian perspective for ecologists, Highlands.

Examples

#library(R2jags)
#library(LOGIT)
#data(medpar)
#JAGS code with J0 as MCMC algorithm
#  out <- J0$BUGS$output
#  myB <- MyBUGSOutput(out, c(uNames("beta", K), "LogL", "AIC", "BIC"))
#  round(myB, 4)