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Under an L0 penalty framework, a computationally efficient implementation of change point detection is developed. By integrating active set algorithms with warm start initialization, the package achieves linear-time complexity for solving change point detection problems. References: Wen et al. (2020) <doi:10.18637/jss.v094.i04>; Zhu et al. (2020)<doi:10.1073/pnas.2014241117>.
| Version: | 0.2.0 |
| Imports: | ggplot2, stats |
| Suggests: | knitr, rmarkdown |
| Published: | 2026-03-23 |
| DOI: | 10.32614/CRAN.package.L0cpt |
| Author: | Tianhao Wang [aut, cre] |
| Maintainer: | Tianhao Wang <tianhaowang at mail.ustc.edu.cn> |
| License: | GPL (≥ 3) |
| NeedsCompilation: | no |
| CRAN checks: | L0cpt results |
| Reference manual: | L0cpt.html , L0cpt.pdf |
| Package source: | L0cpt_0.2.0.tar.gz |
| Windows binaries: | r-devel: L0cpt_0.2.0.zip, r-release: L0cpt_0.2.0.zip, r-oldrel: L0cpt_0.2.0.zip |
| macOS binaries: | r-release (arm64): L0cpt_0.2.0.tgz, r-oldrel (arm64): not available, r-release (x86_64): L0cpt_0.2.0.tgz, r-oldrel (x86_64): L0cpt_0.2.0.tgz |
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