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kcpRS

1.1.1Package record

Kernel Change Point Detection on the Running Statistics

0packages dependsuggested by 1
2.9Kdownloads / year
82.8%test coverage
11/13flavors OK

Overview

About

The running statistics of interest is first extracted using a time window which is slid across the time series, and in each window, the running statistics value is computed. KCP (Kernel Change Point) detection proposed by Arlot et al. (2012) arXiv:1202.3878 is then implemented to flag the change points on the running statistics (Cabrieto et al., 2018, doi:10.1016/j.ins.2018.03.010). Change points are located by minimizing a variance criterion based on the pairwise similarities between running statistics which are computed via the Gaussian kernel. KCP can locate change points for a given k number of change points. To determine the optimal k, the KCP permutation test is first carried out by comparing the variance of the running statistics extracted from the original data to that of permuted data. If this test is significant, then there is sufficient evidence for at least one change point in the data. Model selection is then used to determine the optimal k>0.

Changes in 1.1.1
  • Fix version information in manual page

From NEWS.md in the release

Install

Health

CRAN checks
2NOTE11OK
Check messages
NOTECRAN incoming feasibilityr-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc
Maintainer: ‘Kristof Meers <kristof.meers+cran@kuleuven.be>’

The Description field contains
  detection proposed by Arlot et al. (2012) <arXiv:1202.3878> is then
Please refer to arXiv e-prints via their arXiv DOI <doi:10.48550/arXiv.YYMM.NNNNN>.

CRAN check page ↗

Slowest check: 3.2 min · r-devel-windows-x86_64
Status changes
  • NOTE11 OK, 2 NOTENow
  • NOTE12 OK, 2 NOTE2026-04-22
  • ERROR11 OK, 2 NOTE, 1 ERROR2026-04-18
  • NOTE12 OK, 2 NOTE2026-03-10
Advisories

none known

Documentation

In release 1.1.1
READMENoVignettesNoNEWSYes · 100% structured · mentions 1.1.1Citation fileNoWebsitenot declared in DESCRIPTION
Help pages
12includes a package overview page
Examples that run
100%8 run in a plain check
Exported functions with examples
100%
Documented parameters
100%
Return-value docs
100%
Help pages citing references
58%

Downloads

2.9K
CRAN downloads in the past year
Rank #14,732 · ~8/day · ~242/mo
Daily download trend is not available in this view yet.
26730 days
82090 days
2.9K1 year
Compare downloads with other packages →
Also on340 r2u8 autocran

Dependencies

Declared dependencies
7 external dependencies (excludes base and recommended)

Installing kcpRS adds 8 packages (4 with compiled code, 4.2 MB of source tarballs). Heaviest: Rcpp 1.8 MB, RcppArmadillo 1.0 MB, RcppParallel 744 KB.

Depends (7)
Imports (1)
LinkingTo (1)
Suggests (1)
Enhances (0)
none
Reverse dependencies
0direct
0indirect
Suggested by 1
Suggests, most downloaded first

Datasets

People & History

People (7)
Author, Maintainer since 1.1.0 (2023)
Contributor
Contributor
Contributor
Contributor · added in 1.1.0

Previously maintained by Jedelyn Cabrieto (1.0.0).

Releases (3)

Pick two releases to compare their code metrics.

  • R
    R 4.6.0 released · 2026-04-24
  • R
    R 4.5.0 released · 2025-04-11
  • R
    R 4.4.0 released · 2024-04-24
  • 1.1.1Latest
    record
    2023-10-25 · current release · diff ↗
  • R
    R 4.3.0 released · 2023-04-21
  • 1.1.0
    record
    2023-01-20 · diff ↗
  • R
    R 4.2.0 released · 2022-04-22
  • R
    R 4.1.0 released · 2021-05-18
  • R
    R 4.0.0 released · 2020-04-24
  • 1.0.0
    record
    2019-05-06
  • R
    R 3.6.0 released · 2019-04-26

Package metadata

First published
2019-05-06
Total releases
3 / 7 yrs
License
GPL (>= 2) OSI
Bundled data
19 KB / 2 files
Download size
42 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("kcpRS")
Meers, K., Adolf, J., Cabrieto, J., Ceulemans, E., Kuppens, P., Schat, E., & Tuerlinckx, F. (2023). kcpRS: Kernel Change Point Detection on the Running Statistics (Version 1.1.1) [Computer software]. https://doi.org/10.32614/CRAN.package.kcpRS

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for kcpRS version 1.1.1 [Data set]. HJJB, LLC. Data release v2026-10-25. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-25, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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