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R interface to the 'weightederm' package for 'Python', which provides 'scikit-learn'-style estimators for offline change point regression (data segmentation) via weighted empirical risk minimization. Supports least-squares, Huber, and logistic losses with fixed or cross-validated numbers of change points. Wraps 'Python' via 'reticulate'. Arpino and Venkataramanan (2026) <doi:10.48550/arXiv.2604.11746>.
| Version: | 0.1.0 |
| Imports: | reticulate (≥ 1.28) |
| Suggests: | testthat (≥ 3.0.0) |
| Published: | 2026-04-22 |
| DOI: | 10.32614/CRAN.package.weightederm |
| Author: | Gabriel Arpino [aut, cre] |
| Maintainer: | Gabriel Arpino <arpino.gabriel at gmail.com> |
| BugReports: | https://github.com/gabrielarpino/weightederm-r/issues |
| License: | Apache License (≥ 2.0) |
| URL: | https://github.com/gabrielarpino/weightederm-r |
| NeedsCompilation: | no |
| SystemRequirements: | Python (>= 3.9), weightederm Python package |
| Language: | en-US |
| Materials: | README, NEWS |
| CRAN checks: | weightederm results |
| Reference manual: | weightederm.html , weightederm.pdf |
| Package source: | weightederm_0.1.0.tar.gz |
| Windows binaries: | r-release: weightederm_0.1.0.zip, r-oldrel: weightederm_0.1.0.zip |
| macOS binaries: | r-release (arm64): weightederm_0.1.0.tgz, r-oldrel (arm64): weightederm_0.1.0.tgz, r-release (x86_64): weightederm_0.1.0.tgz, r-oldrel (x86_64): weightederm_0.1.0.tgz |
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These binaries (installable software) and packages are in development.
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