knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.path = "man/figures/README-", out.width = "100%" )
The R package projpred performs the projection predictive variable selection
for various regression models. Usually, the reference model will be 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^[The main vignette can be accessed offline by typing
vignette(topic = "projpred", package = "projpred")
or---more
conveniently---browseVignettes("projpred")
within R.].
For details on how to cite projpred, see the projpred citation
info on CRAN^[The
citation information can be accessed offline by typing
print(citation("projpred"), bibtex = TRUE)
within R.]. Further references
(including earlier work that projpred is based on) are given in section
"Introduction"
of the main vignette.
The vignettes^[The overview of all
vignettes can be accessed offline by typing browseVignettes("projpred")
within
R.] 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^[The
documentation can be accessed offline using ?
or help()
within R.].
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.
install.packages("projpred")
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
.
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