Package: robStepSplitReg 1.1.0

Anthony Christidis

robStepSplitReg: Robust Stepwise Split Regularized Regression

Functions to perform robust stepwise split regularized regression. The approach first uses a robust stepwise algorithm to split the variables into the models of an ensemble. An adaptive robust regularized estimator is then applied to each subset of predictors in the models of an ensemble.

Authors:Anthony Christidis [aut, cre], Gabriela Cohen-Freue [aut]

robStepSplitReg_1.1.0.tar.gz
robStepSplitReg_1.1.0.tar.gz(r-4.5-noble)robStepSplitReg_1.1.0.tar.gz(r-4.4-noble)
robStepSplitReg_1.1.0.tgz(r-4.4-emscripten)robStepSplitReg_1.1.0.tgz(r-4.3-emscripten)
robStepSplitReg.pdf |robStepSplitReg.html
robStepSplitReg/json (API)
NEWS

# Install 'robStepSplitReg' in R:
install.packages('robStepSplitReg', 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

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

openblascpp

2.18 score 1 packages 2 scripts 222 downloads 1 exports 50 dependencies

Last updated 1 years agofrom:4fcf144edd. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKDec 02 2024
R-4.5-linux-x86_64OKDec 02 2024

Exports:robStepSplitReg

Dependencies:cellWiseclicodetoolscolorspaceDEoptimRfansifarverforeachggplot2glmnetgluegridExtragtableisobanditeratorslabelinglatticelifecyclemagrittrMASSMatrixmatrixStatsmgcvmunsellmvtnormnlmepcaPPpillarpkgconfigplyrR6RColorBrewerRcppRcppArmadilloRcppEigenreshape2rlangrobustbaserrcovscalesshapestringistringrsurvivalsvdtibbleutf8vctrsviridisLitewithr