Package: STOPES 0.2

STOPES: Selection Threshold Optimized Empirically via Splitting

Implements variable selection procedures for low to moderate size generalized linear regressions models. It includes the STOPES functions for linear regression (Capanu M, Giurcanu M, Begg C, Gonen M, Optimized variable selection via repeated data splitting, Statistics in Medicine, 2020, 19(6):2167-2184) as well as subsampling based optimization methods for generalized linear regression models (Marinela Capanu, Mihai Giurcanu, Colin B Begg, Mithat Gonen, Subsampling based variable selection for generalized linear models).

Authors:Marinela Capanu [aut, cre], Mihai Giurcanu [aut, ctb], Colin Begg [aut], Mithat Gonen [aut]

STOPES_0.2.tar.gz
STOPES_0.2.zip(r-4.7)STOPES_0.2.zip(r-4.6)STOPES_0.2.zip(r-4.5)
STOPES_0.2.tgz(r-4.6-any)STOPES_0.2.tgz(r-4.5-any)
STOPES_0.2.tar.gz(r-4.7-any)STOPES_0.2.tar.gz(r-4.6-any)
STOPES_0.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
STOPES/json (API)

# Install 'STOPES' in R:
install.packages('STOPES', repos = c('https://capanum.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 195 downloads 4 exports 16 dependencies

Last updated from:5a0d8ee2df. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK162
source / vignettesOK148
linux-release-x86_64OK124
macos-release-arm64OK150
macos-oldrel-arm64OK213
windows-develOK80
windows-releaseOK94
windows-oldrelOK102
wasm-releaseOK106

Exports:alasso.cvoptsopts_thstopes

Dependencies:changepointcodetoolscvToolsDEoptimRforeachglmnetiteratorslatticeMASSMatrixRcppRcppEigenrobustbaseshapesurvivalzoo