changepoints: A Collection of Change-Point Detection Methods

Performs a series of offline and/or online change-point detection algorithms for 1) univariate mean; 2) univariate polynomials; 3) univariate and multivariate nonparametric settings; 4) high-dimensional covariances; 5) high-dimensional networks with and without missing values; 6) high-dimensional linear regression models; 7) high-dimensional vector autoregressive models; 8) high-dimensional self exciting point processes; 9) dependent dynamic nonparametric random dot product graphs; 10) univariate mean against adversarial attacks. For more informations, see <arXiv:1810.09498>; <arXiv:2006.03283>; <arXiv:2007.09910>; <arXiv:1905.10019>; <arXiv:1910.13289>; <arXiv:1712.09912>; <arXiv:1809.09602>; <arXiv:1911.07494>; <arXiv:2101.05477>; <arXiv:2010.10410>; <arXiv:1909.06359>; <arXiv:2006.03572>; <arXiv:2110.06450>; <arXiv:2105.10417>.

Version: 1.0.0
Depends: R (≥ 3.5.0)
Imports: stats, gglasso, glmnet, ks, MASS, data.tree, Rcpp
LinkingTo: Rcpp, RcppArmadillo
Suggests: knitr, abind, DiagrammeR, rmarkdown
Published: 2021-12-10
Author: Haotian Xu [aut, cre], Oscar Padilla [aut], Daren Wang [aut], Mengchu Li [aut], Qin Wen [ctb]
Maintainer: Haotian Xu <haotian.xu at warwick.ac.uk>
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_1.0.0.tar.gz
Windows binaries: r-devel: changepoints_1.0.0.zip, r-release: changepoints_1.0.0.zip, r-oldrel: changepoints_1.0.0.zip
macOS binaries: r-release (arm64): changepoints_1.0.0.tgz, r-release (x86_64): changepoints_1.0.0.tgz, r-oldrel: changepoints_1.0.0.tgz

Linking:

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