fastcpd: Fast Change Point Detection via Sequential Gradient Descent

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: 0.14.1
Depends: R (≥ 2.10)
Imports: fastglm, forecast, glmnet, Matrix, methods, Rcpp (≥ 0.11.0), stats, tseries
LinkingTo: progress, Rcpp, RcppArmadillo, RcppClock, testthat
Suggests: abind, breakfast, changepoint, cpm, CptNonPar, dplyr, fpop, ggplot2, gridExtra, jointseg, knitr, lubridate, matrixStats, mockthat, mvtnorm, not, numDeriv, RcppClock, reshape2, rmarkdown, segmented, stepR, testthat (≥ 3.0.0), VARDetect, wbs, xml2, zoo
Published: 2024-04-18
Author: Xingchi Li ORCID iD [aut, cre, cph], Xianyang Zhang [aut, cph]
Maintainer: Xingchi Li <anthony.li at stat.tamu.edu>
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:

Reference manual: fastcpd.pdf
Vignettes: Comparison with other R packages
Comparison with vanilla PELT
Advanced examples
Custom logistic regression model

Downloads:

Package source: fastcpd_0.14.1.tar.gz
Windows binaries: r-prerel: fastcpd_0.14.1.zip, r-release: fastcpd_0.14.1.zip, r-oldrel: fastcpd_0.14.1.zip
macOS binaries: r-prerel (arm64): fastcpd_0.14.1.tgz, r-release (arm64): fastcpd_0.14.1.tgz, r-oldrel (arm64): fastcpd_0.14.1.tgz, r-prerel (x86_64): fastcpd_0.14.1.tgz, r-release (x86_64): fastcpd_0.14.1.tgz
Old sources: fastcpd archive

Linking:

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