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-any)STOPES_0.2.zip(r-4.6-any)STOPES_0.2.zip(r-4.5-any)
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✨
DESCRIPTION
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 247 downloads 4 exports 16 dependencies

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

TargetResultTimeFilesSyslog
linux-develOK155
source / vignettesOK162
linux-releaseOK133
macos-releaseOK168
macos-oldrelOK159
windows-develOK89
windows-releaseOK86
windows-oldrelOK100
wasm-releaseOK92

Exports:alasso.cvoptsopts_thstopes

Dependencies:changepointcodetoolscvToolsDEoptimRforeachglmnetiteratorslatticeMASSMatrixRcppRcppEigenrobustbaseshapesurvivalzoo