MCMC for Generalized Linear Mixed Models with glmmBUGS

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.

Patrick Brown , Lutong Zhou
2010-6-01

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Citation

For attribution, please cite this work as

Brown & Zhou, "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 = {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}
}