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Provides efficient implementation of the Narrowest-Over-Threshold methodology for detecting an unknown number of change-points occurring at unknown locations in one-dimensional data following 'deterministic signal + noise' model. Currently implemented scenarios are: piecewise-constant signal, piecewise-constant signal with a heavy-tailed noise, piecewise-linear signal, piecewise-quadratic signal, piecewise-constant signal and with piecewise-constant variance of the noise. For details, see Baranowski, Chen and Fryzlewicz (2019) <doi:10.1111/rssb.12322>.
| Version: | 1.6 |
| Depends: | graphics, stats, splines |
| Published: | 2024-09-23 |
| DOI: | 10.32614/CRAN.package.not |
| Author: | Rafal Baranowski [aut], Yining Chen [aut, cre], Piotr Fryzlewicz [aut] |
| Maintainer: | Yining Chen <y.chen101 at lse.ac.uk> |
| License: | GPL-2 |
| NeedsCompilation: | yes |
| CRAN checks: | not results |
| Reference manual: | not.pdf |
| Package source: | not_1.6.tar.gz |
| Windows binaries: | r-devel: not_1.6.zip, r-release: not_1.6.zip, r-oldrel: not_1.6.zip |
| macOS binaries: | r-release (arm64): not_1.6.tgz, r-oldrel (arm64): not_1.6.tgz, r-release (x86_64): not_1.6.tgz, r-oldrel (x86_64): not_1.6.tgz |
| Old sources: | not archive |
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