Authors@R: c(person("Juho", "Piironen", role = c("cre", "aut"), email = "juho.piironen@aalto.fi"),
person("Markus", "Paasiniemi", role = "aut"),
Imports: loo (>= 2.0.0), ggplot2, Rcpp, utils, rngtools (>= 1.2.4)
Suggests: rstanarm, testthat, knitr, rmarkdown, glmnet, bayesplot (>=

person("Paul-Christian", "Bürkner", role = "ctb"))
(see, Piironen, Paasiniemi and Vehtari, 2018, <arXiv:1810.02406>).
The package is compatible with the 'rstanarm' and 'brms' packages, but other
reference models can also be used. See the package vignette for more
Suggests: rstanarm, brms, testthat, knitr, rmarkdown, glmnet, bayesplot

Authors@R: c(person("Juho", "Piironen", role = c("cre", "aut"), email = "juho@cai.fi"),
Packaged: 2019-03-10 14:55:07 UTC; juhopiironen

Imports: loo (>= 2.0.0), ggplot2, Rcpp, utils
Packaged: 2019-05-31 11:59:07 UTC; juhopiironen

Authors@R: c(person("Juho", "Piironen", role = c("cre", "aut"), email = "juho.t.piironen@gmail.com"),
person("Marco", "Colombo", role = "ctb"))

Authors@R: c(person("Juho", "Piironen", role = c("aut"), email = "juho.t.piironen@gmail.com"),
person("Alejandro", "Catalina", role = c("cre", "aut"), email="alecatfel@gmail.com"),
person("Marco", "Colombo", role = "ctb"),
Performs projection predictive feature selection for generalized linear
models and generalized linear and additive multilevel models
(see, Piironen, Paasiniemi and Vehtari, 2020, <https://projecteuclid.org/euclid.ejs/1589335310>,
Catalina, Bürkner and Vehtari, 2020, <arXiv:2010.06994>).
Imports: methods, dplyr, loo (>= 2.0.0), rstantools (>= 2.0.0), lme4,
optimx, ggplot2, Rcpp, utils, rngtools (>= 1.2.4), tidyverse,

Authors@R: c(person("Juho", "Piironen", role = c("aut"),
person("Alejandro", "Catalina", role = "aut",
person("Frank", "Weber", role = c("cre", "aut"),
person("Hamada S.", "Badr", role = "ctb"))
models and 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
mvtnorm, ggplot2, Rcpp, utils, magrittr, mgcv, gamm4, rlang
(>= 1.5.0), optimx, posterior, parallel, foreach, iterators,