R: Two functions to provide better JAGS model output
jhbayes
R Documentation
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.
Note
jhbayes.r must be loaded into memory in order to be effectve. Use the source
function or paste into R editor. Code is 23 lines in length.
Author(s)
Alain F. Zuur, Highlands Statistics, UK. highstat@highstat.com
Joseph M. Hilbe, Arizona State University, and
Jet Propulsion Laboratory, California Institute of technology
hilbe@asu.edu
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)