Package: RChest 1.0.3

Lukas Zierahn

RChest: Locating Distributional Changes in Highly Dependent Time Series

Provides algorithms to locate multiple distributional change-points in piecewise stationary time series. The algorithms are provably consistent, even in the presence of long-range dependencies. Knowledge of the number of change-points is not required. The code is written in Go and interfaced with R.

Authors:Lukas Zierahn [cre, aut], Azadeh Khaleghi [aut]

RChest_1.0.3.tar.gz
RChest_1.0.3.zip(r-4.7)RChest_1.0.3.zip(r-4.6)RChest_1.0.3.zip(r-4.5)
RChest_1.0.3.tgz(r-4.6-any)RChest_1.0.3.tgz(r-4.5-any)
RChest_1.0.3.tar.gz(r-4.7-any)RChest_1.0.3.tar.gz(r-4.6-any)
RChest_1.0.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
RChest/json (API)
NEWS

# Install 'RChest' in R:

install.packages('RChest', repos = c('https://azalk.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/azalk/gochest/issues

On CRAN:

changepoints consistent ergodic long-range-dependence stationary time-series

3.00 score 2 stars 1 scripts 174 downloads 3 exports 14 dependencies

Last updated from:afe9aaf7a8. Checks:7 NOTE, 2 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	NOTE	126
source / vignettes	OK	194
linux-release-x86_64	NOTE	128
macos-release-arm64	NOTE	208
macos-oldrel-arm64	NOTE	189
windows-devel	NOTE	168
windows-release	NOTE	113
windows-oldrel	NOTE	156
wasm-release	OK	110