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, see R. Baranowski, Y. Chen and P. Fryzlewicz (2019) <doi:10.1111/rssb.12322>. 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.
| Version: | 1.2 |
| Depends: | graphics, stats, splines |
| Published: | 2019-07-04 |
| Author: | Rafal Baranowski, Yining Chen, Piotr Fryzlewicz |
| Maintainer: | Rafal Baranowski <package_maintenance at rbaranowski.com> |
| License: | GPL-2 |
| NeedsCompilation: | yes |
| CRAN checks: | not results |
| Reference manual: | not.pdf |
| Package source: | not_1.2.tar.gz |
| Windows binaries: | r-devel: not_1.2.zip, r-release: not_1.2.zip, r-oldrel: not_1.2.zip |
| macOS binaries: | r-release: not_1.2.tgz, r-oldrel: not_1.2.tgz |
| Old sources: | not archive |
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