Package: wbsts 2.1

wbsts: Multiple Change-Point Detection for Nonstationary Time Series

Implements detection for the number and locations of the change-points in a time series using the Wild Binary Segmentation and the Locally Stationary Wavelet model of Korkas and Fryzlewicz (2017) <doi:10.5705/ss.202015.0262>.

Authors:Karolos Korkas and Piotr Fryzlewicz

wbsts_2.1.tar.gz
wbsts_2.1.zip(r-4.5)wbsts_2.1.zip(r-4.4)wbsts_2.1.zip(r-4.3)
wbsts_2.1.tgz(r-4.4-x86_64)wbsts_2.1.tgz(r-4.4-arm64)wbsts_2.1.tgz(r-4.3-x86_64)wbsts_2.1.tgz(r-4.3-arm64)
wbsts_2.1.tar.gz(r-4.5-noble)wbsts_2.1.tar.gz(r-4.4-noble)
wbsts_2.1.tgz(r-4.4-emscripten)wbsts_2.1.tgz(r-4.3-emscripten)
wbsts.pdf |wbsts.html✨
wbsts/json (API)

# Install 'wbsts' in R:
install.packages('wbsts', repos = c('https://kakoko1984.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.23 score 17 scripts 152 downloads 16 exports 3 dependencies

Last updated 4 years agofrom:4945d0b7d2. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 07 2024
R-4.5-win-x86_64OKNov 07 2024
R-4.5-linux-x86_64OKNov 07 2024
R-4.4-win-x86_64OKNov 07 2024
R-4.4-mac-x86_64OKNov 07 2024
R-4.4-mac-aarch64OKNov 07 2024
R-4.3-win-x86_64OKNov 07 2024
R-4.3-mac-x86_64OKNov 07 2024
R-4.3-mac-aarch64OKNov 07 2024

Exports:across_fipcr.rand.max.inner.prodcusumews.transfinner_prod_maxpget.thresget.thres.arhellomulti_across_fippost.processingsim.pw.arsim.pw.ar2sim.pw.armatau.funuh.wbswbs.lsw

Dependencies:mvtnormRcppwavelets