Implements fast change point detection algorithm based on the paper "Sequential Gradient Descent and Quasi-Newton's Method for Change-Point Analysis" by Xianyang Zhang, Trisha Dawn <https://proceedings.mlr.press/v206/zhang23b.html>. The algorithm is based on dynamic programming with pruning and sequential gradient descent. It is able to detect change points a magnitude faster than the vanilla Pruned Exact Linear Time(PELT). The package includes examples of linear regression, logistic regression, Poisson regression, penalized linear regression data, and whole lot more examples with custom cost function in case the user wants to use their own cost function.
Version: 0.16.2 Depends: R (≥ 2.10) Imports: glmnet, Matrix, methods, Rcpp (≥ 0.11.0), stats LinkingTo: progress, Rcpp, RcppArmadillo, RcppEigen, testthat Suggests: ggplot2, gridExtra, knitr, matrixStats, mvtnorm, rmarkdown, testthat (≥ 3.0.0), xml2 Published: 2025-04-25 DOI: 10.32614/CRAN.package.fastcpd Author: Xingchi Li [aut, cre, cph], Xianyang Zhang [aut, cph] Maintainer: Xingchi Li <anthony.li.stat.tamu.edu at lixingchi.com> BugReports: https://github.com/doccstat/fastcpd/issues License: GPL (≥ 3) URL: https://fastcpd.xingchi.li, https://github.com/doccstat/fastcpd NeedsCompilation: yes Citation: fastcpd citation info Materials: README NEWS In views: TimeSeries CRAN checks: fastcpd results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=fastcpd to link to this page.
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