Projection Predictive Feature Selection

Performs projection predictive feature selection for generalized linear models (Piironen, Paasiniemi, and Vehtari, 2020, ) with or without multilevel or additive terms (Catalina, Bürkner, and Vehtari, 2022, < https://proceedings.mlr.press/v151/catalina22a.html>), for some ordinal and nominal regression models (Weber, Glass, and Vehtari, 2025, ), and for many other regression models (using the latent projection by Catalina, Bürkner, and Vehtari, 2021, , which can also be applied to most of the former models). The package is compatible with the 'rstanarm' and 'brms' packages, but other reference models can also be used. See the vignettes and the documentation for more information and examples.


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projpred Stan Logo

The R package projpred performs the projection predictive variable selection for various regression models. Usually, the reference model is an rstanarm or brms fit, but custom reference models can also be used. Details on supported model types are given in section “Supported types of models” of the main vignette[^1].

For details on how to cite projpred, see the projpred citation info on CRAN[^2]. Further references (including earlier work that projpred is based on) are given in section “Introduction” of the main vignette.

The vignettes[^3] illustrate how to use the projpred functions in conjunction. Details on the projpred functions as well as some shorter examples may be found in the documentation[^4].

Installation

There are two ways for installing projpred: from CRAN or from GitHub. The GitHub version might be more recent than the CRAN version, but the CRAN version might be more stable.

From CRAN

install.packages("projpred")

From GitHub

This requires the devtools package, so if necessary, the following code will also install devtools (from CRAN):

if (!requireNamespace("devtools", quietly = TRUE)) {
  install.packages("devtools")
}
devtools::install_github("stan-dev/projpred", build_vignettes = TRUE)

To save time, you may omit build_vignettes = TRUE.

Contributing to projpred

We welcome contributions! The projpred package is under active development. If you find bugs or have ideas for new features (for us or yourself to implement) please open an issue on GitHub. See CONTRIBUTING.md for more details.

[^1]: The main vignette can be accessed offline by typing vignette(topic = "projpred", package = "projpred") or—more conveniently—browseVignettes("projpred") within R.

[^2]: The citation information can be accessed offline by typing print(citation("projpred"), bibtex = TRUE) within R.

[^3]: The overview of all vignettes can be accessed offline by typing browseVignettes("projpred") within R.

[^4]: The documentation can be accessed offline using ? or help() within R.

Reference manual

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install.packages("projpred")

2.11.0 by Osvaldo Martin, 11 days ago


https://mc-stan.org/projpred/, https://discourse.mc-stan.org


Report a bug at https://github.com/stan-dev/projpred/issues/


Browse source code at https://github.com/cran/projpred


Authors: Juho Piironen [aut] , Markus Paasiniemi [aut] , Alejandro Catalina [aut] , Frank Weber [aut] , Osvaldo Martin [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] , The LME4 Authors [cph] (see file 'LICENSE' for details) , Yann McLatchie [ctb] , Juho Timonen [ctb]


Documentation:   PDF Manual  


GPL-3 | file LICENSE license


Imports methods, utils, Rcpp, gtools, ggplot2, scales, rstantools, loo, lme4, mvtnorm, mgcv, gamm4, abind, MASS, ordinal, nnet, mclogit, reformulas

Suggests ggrepel, ggfortify, rstanarm, brms, nlme, optimx, ucminf, parallel, foreach, iterators, doRNG, unix, testthat, vdiffr, knitr, rmarkdown, glmnet, cmdstanr, rlang, bayesplot, posterior, doParallel, future, future.callr, doFuture, progressr

Linking to Rcpp, RcppArmadillo


Imported by bscm.

Suggested by BayesERtools, SignalY, brms.


See at CRAN