Package: not 1.6
not: Narrowest-Over-Threshold Change-Point Detection
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>.
Authors:
not_1.6.tar.gz
not_1.6.zip(r-4.7)not_1.6.zip(r-4.6)not_1.6.zip(r-4.5)
not_1.6.tgz(r-4.6-x86_64)not_1.6.tgz(r-4.6-arm64)not_1.6.tgz(r-4.5-x86_64)not_1.6.tgz(r-4.5-arm64)
not_1.6.tar.gz(r-4.7-arm64)not_1.6.tar.gz(r-4.7-x86_64)not_1.6.tar.gz(r-4.6-arm64)not_1.6.tar.gz(r-4.6-x86_64)
not_1.6.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
not/json (API)
| # Install 'not' in R: |
| install.packages('not', repos = c('https://ychen101.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:9e1b835a82. Checks:13 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 97 | ||
| linux-devel-x86_64 | OK | 106 | ||
| source / vignettes | OK | 137 | ||
| linux-release-arm64 | OK | 91 | ||
| linux-release-x86_64 | OK | 99 | ||
| macos-release-arm64 | OK | 119 | ||
| macos-release-x86_64 | OK | 210 | ||
| macos-oldrel-arm64 | OK | 155 | ||
| macos-oldrel-x86_64 | OK | 350 | ||
| windows-devel | OK | 91 | ||
| windows-release | OK | 75 | ||
| windows-oldrel | OK | 67 | ||
| wasm-release | OK | 98 |
Exports:featuresnotrandom.intervalssic.penalty
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Narrowest-Over-Threshold Change-Point Detection | not-package |
| Akaike Information Criterion penalty | aic.penalty |
| Extract locations of features from a 'not' object | features features.default |
| Extract likelihood from a 'not' object | logLik.not |
| Narrowest-Over-Threshold Change-Point Detection | not not.default |
| Plot a 'not' object | plot.not |
| Estimate signal for a 'not' object. | predict.not |
| Generate random intervals | random.intervals |
| Extract residuals from a 'not' object | residuals.not |
| Schwarz Information Criterion penalty | sic.penalty |
