Package: ggchangepoint
Type: Package
Title: Combines Changepoint Analysis with 'ggplot2'
Version: 0.7.0
Authors@R: 
    c(person(given = "Youzhi",
             family = "Yu",
             role = c("aut", "cre"),
             email = "yuyouzhi666@icloud.com"))
Description: A unified, tidy, 'ggplot2'-native interface to changepoint
    detection in R. A 'cpt_detect()' dispatcher covers 51 methods
    (penalised and optimal partitioning, multiscale and search methods,
    nonparametric and kernel methods, Bayesian methods, high-dimensional,
    functional, covariance and network methods, regression breaks through
    a formula interface, seasonal-trend decomposition, the classical
    single-change tests, and anomalous stretches that return to a
    baseline), with distribution families for counts, binary outcomes and
    waiting times, missing-value handling, grouped data, and constraints
    on locations and segment lengths. Every result is the same 'ggcpt'
    object, in one verified location convention, with 'broom'-style
    tidy/glance/augment methods, 'autoplot()' and composable 'ggproto'
    layers. Around detection: which coordinates of a multivariate series
    changed, certified with family-wise error control; distribution-free
    confidence sets for each location; effect sizes and what the series
    would have done without each change; a test for a change at a date
    fixed in advance, tests for a change anywhere, and screening of many
    series with false discovery rate control; a check of whether a change
    was abrupt or gradual; weights over the number of changes; assumption
    checks and goodness of fit, robustness to the noise model, stability,
    consensus and influence diagnostics, supervised detection, sequential
    monitoring including cumulative-sum and exponentially weighted
    moving-average control charts, power and study design, benchmarks,
    reports and an export under a documented 'JSON' schema. What each
    engine does (its runtime, whether its answer survives a change of
    units or a reversal of time, its false positives by noise regime and
    data type, its false alarms on pure noise) and the calibration of the
    package's own intervals, tests and monitors are measured and shipped
    as data, and 'cpt_recommend()' chooses from those measurements.
    'cpt_register_method()' brings external and non-CRAN detectors into
    the same grammar.
Depends: R (>= 4.0.0)
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Imports: changepoint, changepoint.np, dplyr, ecp, generics, ggplot2 (>=
        3.5.0), lifecycle, Rdpack, stats, tibble, tools, utils
RdMacros: Rdpack
RoxygenNote: 7.3.2
Suggests: rmarkdown, knitr, testthat (>= 3.1.7), withr, rjags, vdiffr,
        svglite, wbs, breakfast, not, mosum, fpop, IDetect, stepR,
        cpop, bcp, ocp, Rbeast, cpm, kcpRS, CptNonPar, DeCAFS, SNSeg,
        InspectChangepoint, ocd, changepoint.geo, strucchange,
        segmented, EnvCpt, fastcpd, nsp, mcp, HDCD, changepoints,
        fChange, KWCChangepoint, fabisearch, NMF, wbsts, bfast, trend,
        ChangePointTaylor, binsegRcpp, crossvalidationCP,
        changepoint.influence, penaltyLearning, anomaly, zoo, xts,
        tsibble, jsonlite, gt, ggrepel, plotly, ggiraph, progressr,
        future, future.apply
Additional_repositories: https://R-Forge.R-project.org,
        https://pursuitofdatascience.github.io/ggchangepoint/repo
Config/testthat/edition: 3
VignetteBuilder: knitr
URL: https://pursuitofdatascience.github.io/ggchangepoint/
BugReports: https://github.com/PursuitOfDataScience/ggchangepoint/issues
Config/Needs/website: rmarkdown
NeedsCompilation: no
Packaged: 2026-11-05 03:02:41 UTC; youzhi
Author: Youzhi Yu [aut, cre]
Maintainer: Youzhi Yu <yuyouzhi666@icloud.com>
Repository: CRAN
Date/Publication: 2026-11-05 04:10:02 UTC
Built: R 4.5.2; ; 2026-11-05 07:03:20 UTC; unix
