Links[{"label":"glmbayes.html","section":"","type":"","url":"https://cran.r-project.org/web/packages/glmbayes/refman/glmbayes.html"},{"label":"glmbayes.pdf","section":"","type":"","url":"https://cran.r-project.org/web/packages/glmbayes/glmbayes.pdf"},{"label":"Chapter 00: Introduction","section":"","type":"","url":"https://cran.r-project.org/web/packages/glmbayes/vignettes/Chapter-00.html"},{"label":"source","section":"","type":"","url":"https://cran.r-project.org/web/packages/glmbayes/vignettes/Chapter-00.Rmd"},{"label":"R code","section":"","type":"","url":"https://cran.r-project.org/web/packages/glmbayes/vignettes/Chapter-00.R"},{"label":"Chapter 01: Getting started with glmbayes","section":"","type":"","url":"https://cran.r-project.org/web/packages/glmbayes/vignettes/Chapter-01.html"},{"label":"source","section":"","type":"","url":"https://cran.r-project.org/web/packages/glmbayes/vignettes/Chapter-01.Rmd"},{"label":"R code","section":"","type":"","url":"https://cran.r-project.org/web/packages/glmbayes/vignettes/Chapter-01.R"},{"label":"Chapter 02-S01: Conjugate Models — Introduction and Overview","section":"","type":"","url":"https://cran.r-project.org/web/packages/glmbayes/vignettes/Chapter-02-S01.html"},{"label":"source","section":"","type":"","url":"https://cran.r-project.org/web/packages/glmbayes/vignettes/Chapter-02-S01.Rmd"},{"label":"R code","section":"","type":"","url":"https://cran.r-project.org/web/packages/glmbayes/vignettes/Chapter-02-S01.R"},{"label":"Chapter 02-S02: Normal–Normal Conjugacy for One Mean","section":"","type":"","url":"https://cran.r-project.org/web/packages/glmbayes/vignettes/Chapter-02-S02.html"},{"label":"source","section":"","type":"","url":"https://cran.r-project.org/web/packages/glmbayes/vignettes/Chapter-02-S02.Rmd"},{"label":"R code","section":"","type":"","url":"https://cran.r-project.org/web/packages/glmbayes/vignettes/Chapter-02-S02.R"},{"label":"Chapter 02-S03: Beta–Binomial Conjugacy for One Proportion","section":"","type":"","url":"https://cran.r-project.org/web/packages/glmbayes/vignettes/Chapter-02-S03.html"},{"label":"source","section":"","type":"","url":"https://cran.r-project.org/web/packages/glmbayes/vignettes/Chapter-02-S03.Rmd"},{"label":"R code","section":"","type":"","url":"https://cran.r-project.org/web/packages/glmbayes/vignettes/Chapter-02-S03.R"},{"label":"Chapter 02-S04: Gamma–Poisson Conjugacy for One Count Rate","section":"","type":"","url":"https://cran.r-project.org/web/packages/glmbayes/vignettes/Chapter-02-S04.html"},{"label":"source","section":"","type":"","url":"https://cran.r-project.org/web/packages/glmbayes/vignettes/Chapter-02-S04.Rmd"},{"label":"R code","section":"","type":"","url":"https://cran.r-project.org/web/packages/glmbayes/vignettes/Chapter-02-S04.R"}]
TextReference manual: glmbayes.html , glmbayes.pdf Vignettes: Chapter 00: Introduction ( source , R code ) Chapter 01: Getting started with glmbayes ( source , R code ) Chapter 02-S01: Conjugate Models — Introduction and Overview ( source , R code ) Chapter 02-S02: Normal–Normal Conjugacy for One Mean ( source , R code ) Chapter 02-S03: Beta–Binomial Conjugacy for One Proportion ( source , R code ) Chapter 02-S04: Gamma–Poisson Conjugacy for One Count Rate ( source , R code ) Chapter 02-S05: Gamma–Gamma Conjugacy for One Response Rate ( source , R code ) Chapter 03: Estimating Bayesian linear models ( source , R code ) Chapter 04: Tailoring priors — leveraging the Prior_Setup function ( source , R code ) Chapter 05: Model predictions and posterior predictive checks (+ bayesplot ppc_*) ( source , R code ) Chapter 06: Deviance residuals, model statistics and posterior inference (+ bayestestR) ( source , R code ) Chapter 07: Foundations of GLMs — families, links, and log-concave likelihoods ( source ) Chapter 08: Estimating Bayesian generalized linear models ( source , R code ) Chapter 09: Models for the Binomial family ( source , R code ) Chapter 10: Models for the Poisson family ( source , R code ) Chapter 11: Models for the Gamma family ( source , R code ) Chapter 12: Visualizing posteriors with bayesplot ( source , R code ) Chapter 13: Bayesian inference and decision making with bayestestR ( source , R code ) Chapter 14: Informative priors — centering and differential prior weights ( source , R code ) Chapter 15: Estimating models with unknown dispersion parameters ( source , R code ) Chapter 16: Large models — GPU acceleration using OpenCL ( source , R code ) Chapter 17: Linear mixed-effects models ( source , R code ) Chapter 18: Generalized linear mixed-effects models ( source , R code ) Chapter A01: A detailed overview of the glmbayes package ( source , R code ) Chapter A02: Overview of Estimation Procedures ( source , R code ) Chapter A03: Methods