changepoints: A Collection of Change-Point Detection Methods

Performs a series of offline and/or online change-point detection algorithms for 1) univariate mean: <doi:10.1214/20-EJS1710>, <arXiv:2006.03283>; 2) univariate polynomials: <doi:10.1214/21-EJS1963>; 3) univariate and multivariate nonparametric settings: <doi:10.1214/21-EJS1809>, <doi:10.1109/TIT.2021.3130330>; 4) high-dimensional covariances: <doi:10.3150/20-BEJ1249>; 5) high-dimensional networks with and without missing values: <doi:10.1214/20-AOS1953>, <arXiv:2101.05477>, <arXiv:2110.06450>; 6) high-dimensional linear regression models: <arXiv:2010.10410>, <arXiv:2207.12453>; 7) high-dimensional vector autoregressive models: <arXiv:1909.06359>; 8) high-dimensional self exciting point processes: <arXiv:2006.03572>; 9) dependent dynamic nonparametric random dot product graphs: <arXiv:1911.07494>; 10) univariate mean against adversarial attacks: <arXiv:2105.10417>.

Version: 1.1.0
Depends: R (≥ 3.5.0)
Imports: stats, gglasso, glmnet, ks, MASS, data.tree, Rcpp
LinkingTo: Rcpp, RcppArmadillo
Suggests: knitr, abind, DiagrammeR, rmarkdown
Published: 2022-09-04
Author: Haotian Xu [aut, cre], Oscar Padilla [aut], Daren Wang [aut], Mengchu Li [aut], Qin Wen [ctb]
Maintainer: Haotian Xu <haotian.xu at uclouvain.be>
License: GPL (≥ 3)
URL: https://github.com/HaotianXu/changepoints
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: changepoints results

Documentation:

Reference manual: changepoints.pdf
Vignettes: example_VAR
example_univariate_mean

Downloads:

Package source: changepoints_1.1.0.tar.gz
Windows binaries: r-devel: changepoints_1.1.0.zip, r-release: changepoints_1.1.0.zip, r-oldrel: changepoints_1.1.0.zip
macOS binaries: r-release (arm64): changepoints_1.1.0.tgz, r-oldrel (arm64): changepoints_1.1.0.tgz, r-release (x86_64): changepoints_1.1.0.tgz
Old sources: changepoints archive

Linking:

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