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VARcpDetectOnline

0.2.1Package record

Sequential Change Point Detection for High-Dimensional VAR Models

0packages depend
3Kdownloads / year
–test coverage
13/13flavors OK

Overview

About

Implements the algorithm introduced in Tian, Y., and Safikhani, A. (2024) doi:10.5705/ss.202024.0182, "Sequential Change Point Detection in High-dimensional Vector Auto-regressive Models". This package provides tools for detecting change points in the transition matrices of VAR models, effectively identifying shifts in temporal and cross-correlations within high-dimensional time series data.

Changes in 0.2.1
  • Email updated.

From NEWS.md in the release

Install

Health

CRAN checks
13OK
Slowest check: 1.1 min · r-oldrel-windows-x86_64
Status changes
  • OK13 OK2026-09-08
  • ERROR12 OK, 1 ERROR2026-09-07
  • OK13 OK2026-08-05
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK14 OK2026-03-10
Advisories

none known

Documentation

In release 0.2.1
READMENoVignettesNoNEWSYes · 100% structured · mentions 0.2.1Citation fileNoWebsitenot declared in DESCRIPTION
Help pages
13 (8 internal)
Examples that run
75%3 run in a plain check · 1 only when donttest examples are enabled (R CMD check --as-cran)
Exported functions with examples
75%
Documented parameters
100%
Return-value docs
100%
Help pages citing references
8%

Downloads

3K
CRAN downloads in the past year
Rank #9,903 · ~8/day · ~251/mo
Daily download trend is not available in this view yet.
Also on140 r2u5 autocran

Repository

3Stars
0Forks
1Open issues
0Open PRs
0Releases
5Commits
1Commit identities
5 commits · Last activity 2025-02-12 · 0% stars, 30d · The default branch showed an older version (0.2.0) than CRAN on 2026-10-21
Responsiveness
not measured

Stars over time

2025-02-15 · 32026-07-07 · 3
PracticesBeta

1 development-tooling and community-health practice detected across 1 family in the upstream repository

Checks run against github.com/helloworld9293/varcpdetectonline on 2026-10-21.

Lint, format, editor (1)
RStudio project
How this is detected·Detection ruleset v4 (2026-10-20)

Dependencies

Declared dependencies
4 external dependencies (excludes base and recommended)

Installing VARcpDetectOnline adds 8 packages (3 with compiled code, 7.4 MB of source tarballs). Heaviest: glmnet 2.7 MB, Rcpp 1.8 MB, RcppEigen 1.7 MB.

Depends (1)
R >= 3.5.0
Imports (6)
LinkingTo (0)
none
Suggests (1)
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Datasets

People & History

People (2)
Author, Maintainer since 0.1.0 (2025)
Releases (3)

Pick two releases to compare their code metrics.

  • 0.2.1Latest
    record
    2026-07-02 · current release · diff ↗
  • R
    R 4.6.0 released · 2026-04-24
  • R
    R 4.5.0 released · 2025-04-11
  • unarchivedReturned to CRAN
    2025-02-13
  • 0.2.0
    record
    2025-02-13 · diff ↗ ·
    added 1 export
    fitVAR
  • archivedRemoved from CRAN
    2025-02-09
    requires archived package 'sparsevar'
  • 0.1.0
    record
    2025-01-09
  • R
    R 4.4.0 released · 2024-04-24

Package metadata

First published
2025-01-09
Total releases
3 / 1 yrs
License
GPL-2 | file LICENSE OSI · relicensed from MIT + file LICENSE in 0.2.0
Minimum R
≥ 3.5.0
Bundled data
4.1 MB / 1 file
Download size
4.1 MB
Appears in task views

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("VARcpDetectOnline")
Tian, Y., & Safikhani, A. (2026). VARcpDetectOnline: Sequential Change Point Detection for High-Dimensional VAR Models (Version 0.2.1) [Computer software]. https://doi.org/10.32614/CRAN.package.VARcpDetectOnline

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 VARcpDetectOnline version 0.2.1 [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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