Package: wbs 1.4.1
Rafal Baranowski
wbs: Wild Binary Segmentation for Multiple Change-Point Detection
Provides efficient implementation of the Wild Binary Segmentation and Binary Segmentation algorithms for estimation of the number and locations of multiple change-points in the piecewise constant function plus Gaussian noise model.
Authors:
wbs_1.4.1.tar.gz
wbs_1.4.1.tar.gz(r-4.5-noble)wbs_1.4.1.tar.gz(r-4.4-noble)
wbs_1.4.1.tgz(r-4.4-emscripten)wbs_1.4.1.tgz(r-4.3-emscripten)
wbs.pdf |wbs.html✨
wbs/json (API)
| # Install 'wbs' in R: |
| install.packages('wbs', repos = c('https://cran.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 2 months agofrom:8b03281e4d. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Dec 05 2024 |
| R-4.5-linux-x86_64 | OK | Dec 05 2024 |
Exports:changepointsfixed.intervalsmeans.between.cptrandom.intervalssbsssic.penaltywbs
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Wild Binary Segmentation for multiple change-point detection | wbs-package |
| Bayesian Information Criterion penalty term | bic.penalty |
| Change-points detected by WBS or BS | changepoints changepoints.sbs changepoints.wbs |
| Fixed intervals | fixed.intervals |
| Modified Bayes Information Criterion penalty term | mbic.penalty |
| Means between change-points | means.between.cpt |
| Plot for an 'sbs' object | plot.sbs |
| Plot for a 'wbs' object | plot.wbs |
| Print for an 'sbs' object | print.sbs |
| Print for a 'wbs' object | print.wbs |
| Random intervals | random.intervals |
| Change-point detection via standard Binary Segmentation | sbs sbs.default |
| Strengthened Schwarz Information Criterion penalty term | ssic.penalty |
| Change-point detection via Wild Binary Segmentation | wbs wbs.default |