The glmmBUGS package is a bridging tool between Generalized Linear Mixed Models (GLMMs) in R and the BUGS language. It provides a simple way of performing Bayesian inference using Markov Chain Monte Carlo (MCMC) methods, taking a model formula and data frame in R and writing a BUGS model file, data file, and initial values files. Functions are provided to reformat and summarize the BUGS results. A key aim of the package is to provide files and objects that can be modified prior to calling BUGS, giving users a platform for customizing and extending the models to accommodate a wide variety of analyses.
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For attribution, please cite this work as
Brown & Zhou, "The R Journal: MCMC for Generalized Linear Mixed Models with glmmBUGS", The R Journal, 2010
BibTeX citation
@article{RJ-2010-003,
author = {Brown, Patrick and Zhou, Lutong},
title = {The R Journal: MCMC for Generalized Linear Mixed Models with glmmBUGS},
journal = {The R Journal},
year = {2010},
note = {https://doi.org/10.32614/RJ-2010-003},
doi = {10.32614/RJ-2010-003},
volume = {2},
issue = {1},
issn = {2073-4859},
pages = {13-17}
}