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DESCRIPTION
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DESCRIPTION
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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