Implements the multiple changepoint algorithm PELT with a nonparametric cost function based on the empirical distribution of the data. This package extends the changepoint package (see Killick, R and Eckley, I (2014) <doi:10.18637/jss.v058.i03> ).
Kaylea Haynes [aut],
Rebecca Killick [aut],
Paul Fearnhead [ths, ctb],
Idris Eckley [ths],
Daniel Grose [ctb, cre]

Change Point Tests for Joint Distributions and Copulas
c( person(c("Bouchra","R"), "Nasri", role = c("aut"), email = "bouchra.nasri@umontreal.ca"),
person(c("Bruno","N"), "Remillard", role = c("aut", "cre","cph"),email = "bruno.remillard@hec.ca"))
Change point tests for joint distributions and copulas using pseudo-observations with multipliers or bootstrap. The processes used here have been defined in Bucher, Kojadinovic, Rohmer & Segers <doi:10.1016/j.jmva.2014.07.012> and Nasri & Remillard <doi:10.1016/j.jmva.2019.03.002>.
Bouchra R Nasri [aut],
Bruno N Remillard [aut, cre, cph]

A Collection of Change-Point Detection Methods
c(
person("Haotian", "Xu", email="haotian.xu@warwick.ac.uk", 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")
)
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>.
stats, gglasso, glmnet, ks, MASS, data.tree, Rcpp
Haotian Xu [aut, cre],
Oscar Padilla [aut],
Daren Wang [aut],
Mengchu Li [aut],
Qin Wen [ctb]