Package: changepoints
Type: Package
Title: A Collection of Change-Point Detection Methods
Version: 1.1.0
Date: 2022-12-29
Authors@R: c(
    person("Haotian", "Xu", email="haotian.xu@uclouvain.be", role=c("aut","cre")),
    person("Oscar", "Padilla", email="oscar.madrid@stat.ucla.edu", role="aut"),
    person("Daren", "Wang", email="dwang24@nd.edu", role="aut"),
    person("Mengchu", "Li", email="Mengchu.Li@warwick.ac.uk", role="aut"),
    person("Qin", "Wen", role="ctb")
    )
Maintainer: Haotian Xu <haotian.xu@uclouvain.be>
Description: 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>.
Depends: R (>= 3.5.0)
Imports: stats, gglasso, glmnet, MASS, Rcpp, data.tree, cubature
Suggests: knitr, abind, rmarkdown
LinkingTo: Rcpp, RcppArmadillo
License: GPL (>= 3)
RoxygenNote: 7.2.3
Encoding: UTF-8
URL: https://github.com/HaotianXu/changepoints
VignetteBuilder: knitr
Config/pak/sysreqs: make libicu-dev
Repository: https://haotianxu.r-universe.dev
Date/Publication: 2023-10-07 11:28:54 UTC
RemoteUrl: https://github.com/haotianxu/changepoints
RemoteRef: HEAD
RemoteSha: 002b97ea4e29b38dbd55ccfcbbf24ffeccfd9532
NeedsCompilation: yes
Packaged: 2026-06-14 09:48:04 UTC; root
Author: Haotian Xu [aut, cre],
  Oscar Padilla [aut],
  Daren Wang [aut],
  Mengchu Li [aut],
  Qin Wen [ctb]