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-4.4-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)

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4 exports 0.00 score 16 dependencies 162 downloads

Last updated 2 years agofrom:5a0d8ee2df. Checks:OK: 7. Indexed: yes.

Exports:alasso.cvoptsopts_thstopes

Dependencies:changepointcodetoolscvToolsDEoptimRforeachglmnetiteratorslatticeMASSMatrixRcppRcppEigenrobustbaseshapesurvivalzoo