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stepSplitReg
View on CRAN: Click
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Download and install stepSplitReg package within the R console
Install from CRAN:
install.packages("stepSplitReg")
Install from Github:
library("remotes")
install_github("cran/stepSplitReg") Install by package version:
library("remotes")
install_version("stepSplitReg", "1.0.5") Attach the package and use:
library("stepSplitReg")
Maintained by
Anthony Christidis
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[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-03-07
Latest Update: 2025-03-30
Description:
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.
How to cite:
Anthony Christidis (2022). stepSplitReg: Stepwise Split Regularized Regression. R package version 1.0.5, https://cran.r-project.org/web/packages/stepSplitReg. Accessed 18 Sep. 2026.
Previous versions and publish date:
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Complete documentation for stepSplitReg
Functions, R codes and Examples using
the stepSplitReg R package
Some associated functions: coef.cv.stepSplitReg . coef.stepSplitReg . cv.stepSplitReg . predict.cv.stepSplitReg . predict.stepSplitReg . stepSplitReg .
Some associated R codes: CV_stepSplitReg.R . Coefficients.R . Create_Folds.R . Data_Check.R . Predictions.R . RcppExports.R . Stacking.R . stepSplitReg.R . Full stepSplitReg package functions and examples
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