Package: stepSplitReg 1.0.3

Anthony Christidis

stepSplitReg: Stepwise Split Regularized Regression

Functions to perform stepwise split regularized regression. The approach first uses a stepwise algorithm to split the variables into the models with a goodness of fit criterion, and then regularization is applied to each model. The weights of the models in the ensemble are determined based on a criterion selected by the user.

Authors:Anthony Christidis [aut, cre], Stefan Van Aelst [aut], Ruben Zamar [aut]

stepSplitReg_1.0.3.tar.gz
stepSplitReg_1.0.3.tar.gz(r-4.5-noble)stepSplitReg_1.0.3.tar.gz(r-4.4-noble)
stepSplitReg_1.0.3.tgz(r-4.4-emscripten)stepSplitReg_1.0.3.tgz(r-4.3-emscripten)
stepSplitReg.pdf |stepSplitReg.html
stepSplitReg/json (API)
NEWS

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

Peer review:

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

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

openblascppopenmp

1.70 score 2 scripts 215 downloads 2 exports 4 dependencies

Last updated 2 years agofrom:3f547d7b23. Checks:OK: 1 ERROR: 1. Indexed: no.

TargetResultDate
Doc / VignettesOKDec 02 2024
R-4.5-linux-x86_64ERRORDec 02 2024

Exports:cv.stepSplitRegstepSplitReg

Dependencies:nnlsRcppRcppArmadilloSplitGLM