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: Estimating Bayesian Linear Models","section":"","type":"","url":"https://cran.r-project.org/web/packages/glmbayes/vignettes/Chapter-02.html"},{"label":"source","section":"","type":"","url":"https://cran.r-project.org/web/packages/glmbayes/vignettes/Chapter-02.Rmd"},{"label":"R code","section":"","type":"","url":"https://cran.r-project.org/web/packages/glmbayes/vignettes/Chapter-02.R"},{"label":"Chapter 03: Tailoring Priors - Leveraging the Prior_Setup Function","section":"","type":"","url":"https://cran.r-project.org/web/packages/glmbayes/vignettes/Chapter-03.html"},{"label":"source","section":"","type":"","url":"https://cran.r-project.org/web/packages/glmbayes/vignettes/Chapter-03.Rmd"},{"label":"R code","section":"","type":"","url":"https://cran.r-project.org/web/packages/glmbayes/vignettes/Chapter-03.R"},{"label":"Chapter 04: Reviewing Model Predictions, Deviance Residuals and Model Statistics","section":"","type":"","url":"https://cran.r-project.org/web/packages/glmbayes/vignettes/Chapter-04.html"},{"label":"source","section":"","type":"","url":"https://cran.r-project.org/web/packages/glmbayes/vignettes/Chapter-04.Rmd"},{"label":"R code","section":"","type":"","url":"https://cran.r-project.org/web/packages/glmbayes/vignettes/Chapter-04.R"},{"label":"Chapter 05: Foundations of GLMs – Families, Links, and Log-Concave Likelihoods","section":"","type":"","url":"https://cran.r-project.org/web/packages/glmbayes/vignettes/Chapter-05.html"},{"label":"source","section":"","type":"","url":"https://cran.r-project.org/web/packages/glmbayes/vignettes/Chapter-05.Rmd"},{"label":"Chapter 06: Estimating Bayesian Generalized Linear Models","section":"","type":"","url":"https://cran.r-project.org/web/packages/glmbayes/vignettes/Chapter-06.html"}]
TextReference manual: glmbayes.html , glmbayes.pdf Vignettes: Chapter 00: Introduction ( source , R code ) Chapter 01: Getting started with glmbayes ( source , R code ) Chapter 02: Estimating Bayesian Linear Models ( source , R code ) Chapter 03: Tailoring Priors - Leveraging the Prior_Setup Function ( source , R code ) Chapter 04: Reviewing Model Predictions, Deviance Residuals and Model Statistics ( source , R code ) Chapter 05: Foundations of GLMs – Families, Links, and Log-Concave Likelihoods ( source ) Chapter 06: Estimating Bayesian Generalized Linear Models ( source , R code ) Chapter 07: Models for the Binomial Family ( source , R code ) Chapter 08: Models for the Poisson Family ( source , R code ) Chapter 09: Models for the Gamma Family ( source , R code ) Chapter 10: Informative Priors: Centering and priors with differentiated prior weights ( source , R code ) Chapter 11: Estimating Models with unknown dispersion parameters ( source , R code ) Chapter 12: Large Models: GPU Acceleration using OpenCL ( source , R code ) Chapter 13: Hierarchical Linear Models ( source , R code ) Chapter 14: Hierarchical Generalized Linear 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 available in glmbayes ( source , R code ) Chapter A04: Directional Tail Diagnostics for Prior-Posterior Disagreement ( source , R code ) Chapter A05: Simulation Methods - Likelihood Subgradient Densities ( source , R code ) Chapter A06: Accept–Reject Sampling for Dispersion in Gamma Regression ( source , R code ) Chapter A07: Accept–Reject Sampling for gaussian Regression models with independent normal-gamma priors ( source , R code ) Chapter A08: Overview of Envelope Related Functions ( source , R code ) Chapter A09: Parallel Sampling Implementation using RcppParallel ( source , R code ) Chapter A10: Accelerated EnvelopeBuild Implementation using Ope