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-4.5)STOPES_0.2.zip(r-4.4)STOPES_0.2.zip(r-4.3)
STOPES_0.2.tgz(r-4.5-any)STOPES_0.2.tgz(r-4.4-any)STOPES_0.2.tgz(r-4.3-any)
STOPES_0.2.tar.gz(r-4.5-noble)STOPES_0.2.tar.gz(r-4.4-noble)
STOPES_0.2.tgz(r-4.4-emscripten)STOPES_0.2.tgz(r-4.3-emscripten)
STOPES.pdf |STOPES.html
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 124 downloads 4 exports 16 dependencies

Last updated 3 years agofrom:5a0d8ee2df. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 16 2025
R-4.5-winOKMar 16 2025
R-4.5-macOKMar 16 2025
R-4.5-linuxOKMar 16 2025
R-4.4-winOKMar 16 2025
R-4.4-macOKMar 16 2025
R-4.4-linuxOKMar 16 2025
R-4.3-winOKMar 16 2025
R-4.3-macOKMar 16 2025

Exports:alasso.cvoptsopts_thstopes

Dependencies:changepointcodetoolscvToolsDEoptimRforeachglmnetiteratorslatticeMASSMatrixRcppRcppEigenrobustbaseshapesurvivalzoo