doi:10.1214/20-EJS1710>, <doi:10.48550/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>, <doi:10.48550/arXiv.2101.05477>, <doi:10.48550/arXiv.2110.06450>; 6) high-dimensional linear regression models: <doi:10.48550/arXiv.2010.10410>, <doi:10.48550/arXiv.2207.12453>; 7) high-dimensional vector autoregressive models: <doi:10.48550/arXiv.1909.06359>; 8) high-dimensional self exciting point processes: <doi:10.48550/arXiv.2006.03572>; 9) dependent dynamic nonparametric random dot product graphs: <doi:10.48550/arXiv.1911.07494>; 10) univariate mean against adversarial attacks: <doi:10.48550/arXiv.2105.10417>.">

changepoints: A Collection of Change-Point Detection Methods (original) (raw)

Performs a series of offline and/or online change-point detection algorithms for 1) univariate mean: <doi:10.1214/20-EJS1710>, <doi:10.48550/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>, <doi:10.48550/arXiv.2101.05477>, <doi:10.48550/arXiv.2110.06450>; 6) high-dimensional linear regression models: <doi:10.48550/arXiv.2010.10410>, <doi:10.48550/arXiv.2207.12453>; 7) high-dimensional vector autoregressive models: <doi:10.48550/arXiv.1909.06359>; 8) high-dimensional self exciting point processes: <doi:10.48550/arXiv.2006.03572>; 9) dependent dynamic nonparametric random dot product graphs: <doi:10.48550/arXiv.1911.07494>; 10) univariate mean against adversarial attacks: <doi:10.48550/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
DOI: 10.32614/CRAN.package.changepoints
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

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