DESCRIPTION

Type: Package
Package: fastcpd
Title: Fast Change Point Detection via Sequential Gradient Descent
Version: 0.14.7
Authors@R: c(
    person("Xingchi", "Li", , "anthony.li@stat.tamu.edu",
           role = c("aut", "cre", "cph"),
           comment = c(ORCID = "0009-0006-2493-0853")),
    person("Xianyang", "Zhang", , "zhangxiany@stat.tamu.edu",
           role = c("aut", "cph"))
  )
Description: 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.
License: GPL (>= 3)
URL: https://fastcpd.xingchi.li, https://github.com/doccstat/fastcpd
BugReports: https://github.com/doccstat/fastcpd/issues
Depends:
    R (>= 2.10)
Imports:
    fastglm,
    forecast,
    glmnet,
    Matrix,
    methods,
    Rcpp (>= 0.11.0),
    stats,
    tseries
Suggests:
    abind,
    dplyr,
    ggplot2,
    gridExtra,
    knitr,
    lubridate,
    matrixStats,
    mockthat,
    mvtnorm,
    numDeriv,
    RcppClock,
    reshape2,
    rmarkdown,
    testthat (>= 3.0.0),
    xml2,
    zoo
LinkingTo:
    progress,
    Rcpp,
    RcppArmadillo,
    RcppClock,
    testthat
VignetteBuilder:
    knitr
Config/testthat/edition: 3
Config/testthat/parallel: true
Config/testthat/start-first:
    vignettes-comparison-pelt,
    examples-fastcpd_arima,
    examples-fastcpd_ts
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.3.1