SplitWise: 'SplitWise': Hybrid Stepwise Regression with Single-Split Dummy Encoding

Implements 'SplitWise', a hybrid regression approach that transforms numeric variables into either single-split (0/1) dummy variables or retains them as continuous predictors. The transformation is followed by stepwise selection to identify the most relevant variables. The default 'iterative' mode adaptively explores partial synergies among variables to enhance model performance, while an alternative 'univariate' mode applies simpler transformations independently to each predictor. For details, see Kurbucz et al. (2025) <doi:10.48550/arXiv.2505.15423>.

Version:	1.0.0
Depends:	R (≥ 3.5.0)
Imports:	rpart, stats
Suggests:	knitr, rmarkdown, testthat (≥ 3.0.0)
Published:	2025-05-28
DOI:	10.32614/CRAN.package.SplitWise
Author:	Marcell T. Kurbucz [aut, cre], Nikolaos Tzivanakis [aut], Nilufer Sari Aslam [aut], Adam Sykulski [aut]
Maintainer:	Marcell T. Kurbucz <m.kurbucz at ucl.ac.uk>
License:	GPL (≥ 3)
NeedsCompilation:	no
Materials:	README
CRAN checks:	SplitWise results

Documentation:

Reference manual:	SplitWise.pdf
Vignettes:	Using the SplitWise Package with the mtcars Dataset (source, R code)

Downloads:

Package source:	SplitWise_1.0.0.tar.gz
Windows binaries:	r-devel: not available, r-release: SplitWise_1.0.0.zip, r-oldrel: SplitWise_1.0.0.zip
macOS binaries:	r-release (arm64): SplitWise_1.0.0.tgz, r-oldrel (arm64): SplitWise_1.0.0.tgz, r-release (x86_64): SplitWise_1.0.0.tgz, r-oldrel (x86_64): SplitWise_1.0.0.tgz

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