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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 |
| Reference manual: | SplitWise.pdf |
| Vignettes: |
Using the SplitWise Package with the mtcars Dataset (source, R code) |
| Package source: | SplitWise_1.0.0.tar.gz |
| Windows binaries: | r-devel: not available, r-release: not available, r-oldrel: not available |
| 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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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.