Performs projection predictive feature selection for generalized linear and
additive models as well as for generalized linear and additive multilevel
models (see Piironen, Paasiniemi and Vehtari, 2020,
<doi:10.1214/20-EJS1711>; Catalina, Bürkner and Vehtari, 2020,
<arXiv:2010.06994>). The package is compatible with the 'rstanarm' and
'brms' packages, but other reference models can also be used. See the
documentation as well as the package vignette for more information and
examples.
rstanarm, brms, testthat, knitr, rmarkdown, glmnet, cmdstanr,
bayesplot (>= 1.5.0), optimx, posterior, parallel, foreach,
iterators, doParallel, future, future.callr, doFuture

c(person("Juho", "Piironen", role = c("aut"),
email = "juho.t.piironen@gmail.com"),
person("Markus", "Paasiniemi", role = "aut"),
person("Alejandro", "Catalina", role = "aut",
email = "alecatfel@gmail.com"),
person("Frank", "Weber", role = c("cre", "aut"),
email = "fweber144@protonmail.com"),
person("Aki", "Vehtari", role = "aut"),
person("Jonah", "Gabry", role = "ctb"),
person("Marco", "Colombo", role = "ctb"),
person("Paul-Christian", "Bürkner", role = "ctb"),
person("Hamada S.", "Badr", role = "ctb"),
person("Brian", "Sullivan", role = "ctb"))
Juho Piironen [aut],
Markus Paasiniemi [aut],
Alejandro Catalina [aut],
Frank Weber [cre, aut],
Aki Vehtari [aut],
Jonah Gabry [ctb],
Marco Colombo [ctb],
Paul-Christian Bürkner [ctb],
Hamada S. Badr [ctb],
Brian Sullivan [ctb]

c(person("Juho", "Piironen", role = c("aut"),
email = "juho.t.piironen@gmail.com"),
person("Markus", "Paasiniemi", role = "aut"),
person("Alejandro", "Catalina", role = "aut",
email = "alecatfel@gmail.com"),
person("Frank", "Weber", role = c("cre", "aut"),
email = "fweber144@protonmail.com"),
person("Aki", "Vehtari", role = "aut"),
person("Jonah", "Gabry", role = "ctb"),
person("Marco", "Colombo", role = "ctb"),
person("Paul-Christian", "Bürkner", role = "ctb"),
person("Hamada S.", "Badr", role = "ctb"),
person("Brian", "Sullivan", role = "ctb"),
person("Sölvi", "Rögnvaldsson", role = "ctb"))
Performs projection predictive feature selection for generalized linear and
additive models as well as for generalized linear and additive multilevel
models (see Piironen, Paasiniemi and Vehtari, 2020,
<doi:10.1214/20-EJS1711>; Catalina, Bürkner and Vehtari, 2022,
<https://proceedings.mlr.press/v151/catalina22a.html>). The package is
compatible with the 'rstanarm' and 'brms' packages, but other reference
models can also be used. See the documentation as well as the package
vignette for more information and examples.
methods, dplyr, loo (>= 2.0.0), rstantools (>= 2.0.0), lme4,
mvtnorm, ggplot2, Rcpp, utils, magrittr, mgcv, gamm4, MASS,
rlang
rstanarm, brms, testthat, knitr, rmarkdown, glmnet, cmdstanr,
bayesplot (>= 1.5.0), nlme, optimx, posterior, parallel,
foreach, iterators, doParallel, future, future.callr, doFuture
Juho Piironen [aut],
Markus Paasiniemi [aut],
Alejandro Catalina [aut],
Frank Weber [cre, aut],
Aki Vehtari [aut],
Jonah Gabry [ctb],
Marco Colombo [ctb],
Paul-Christian Bürkner [ctb],
Hamada S. Badr [ctb],
Brian Sullivan [ctb],
Sölvi Rögnvaldsson [ctb]