Fits linear or generalized linear regression models using Bayesian global-local shrinkage prior hierarchies as described in Polson and Scott (2010) <doi:10.1093/acprof:oso/9780199694587.003.0017>. Provides an efficient implementation of ridge, lasso, horseshoe and horseshoe+ regression with logistic, Gaussian, Laplace, Student-t, Poisson or geometric distributed targets using the algorithms summarized in Makalic and Schmidt (2016) <arXiv:1611.06649>.
c(
person("Daniel F. Schmidt", email="daniel.schmidt@monash.edu", role = c("aut","cph","cre"), comment = c(ORCID = "0000-0002-1788-2375")),
person("Enes Makalic", email="emakalic@unimelb.edu.au", role=c("aut","cph"), comment = c(ORCID = "0000-0003-3017-0871"))
)
Daniel F. Schmidt [aut, cph, cre]
(<https://orcid.org/0000-0002-1788-2375>),
Enes Makalic [aut, cph] (<https://orcid.org/0000-0003-3017-0871>)

Datasets and Supplemental Functions from Bayes Rules! Book
c(
person("Mine", "Dogucu", , "mdogucu@gmail.com", c("aut", "cre"), comment = c(ORCID = "0000-0002-8007-934X")),
person("Alicia", "Johnson", , role = "aut"),
person("Miles", "Ott", , role = "aut", comment = c(ORCID = "0000-0003-4457-6565"))
)
Provides datasets and functions used for analysis
and visualizations in the Bayes Rules! book (<https://www.bayesrulesbook.com>).
The package contains a set of functions that summarize and plot Bayesian models from some conjugate families
and another set of functions for evaluation of some Bayesian models.
ggplot2, janitor, magrittr, dplyr, stats, purrr, rstanarm,
e1071, groupdata2
Mine Dogucu [aut, cre] (<https://orcid.org/0000-0002-8007-934X>),
Alicia Johnson [aut],
Miles Ott [aut] (<https://orcid.org/0000-0003-4457-6565>)

Christian P. Robert, Universite Paris Dauphine, and Jean-Michel
Marin, Universite Montpellier 2
bayess contains a collection of functions that allows the
reenactment of the R programs used in the book "Bayesian
Essentials with R" (revision of "Bayesian Core") without
further programming. R code being available as well, they can
be modified by the user to conduct one's own simulations.