Package: stepSplitReg 1.0.4

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_1.0.4.tar.gz
stepSplitReg_1.0.4.zip(r-4.7)stepSplitReg_1.0.4.zip(r-4.6)stepSplitReg_1.0.4.zip(r-4.5)
stepSplitReg_1.0.4.tgz(r-4.6-x86_64)stepSplitReg_1.0.4.tgz(r-4.6-arm64)stepSplitReg_1.0.4.tgz(r-4.5-x86_64)stepSplitReg_1.0.4.tgz(r-4.5-arm64)
stepSplitReg_1.0.4.tar.gz(r-4.7-arm64)stepSplitReg_1.0.4.tar.gz(r-4.7-x86_64)stepSplitReg_1.0.4.tar.gz(r-4.6-arm64)stepSplitReg_1.0.4.tar.gz(r-4.6-x86_64)
stepSplitReg_1.0.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
stepSplitReg/json (API)

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

Bug tracker:https://github.com/anthonychristidis/stepsplitreg/issues

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

On CRAN:

Conda:

openblascppopenmp

2.70 score 2 scripts 259 downloads 2 exports 4 dependencies

Last updated from:8cbb09ed77. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK151
linux-devel-x86_64OK161
source / vignettesOK225
linux-release-arm64OK144
linux-release-x86_64OK145
macos-release-arm64OK156
macos-release-x86_64OK264
macos-oldrel-arm64OK102
macos-oldrel-x86_64OK460
windows-develOK174
windows-releaseOK144
windows-oldrelOK137
wasm-releaseOK119

Exports:cv.stepSplitRegstepSplitReg

Dependencies:nnlsRcppRcppArmadilloSplitGLM