VARcpDetectOnline: Sequential Change Point Detection for High-Dimensional VAR Models

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 Vector Auto-Regressive (VAR) models, effectively identifying shifts in temporal and cross-correlations within high-dimensional time series data. The package includes functions to generate synthetic VAR data, detect change points in high-dimensional time series, and analyze real-world data. It also demonstrates an application to financial data: the daily log returns of 186 S&P 500 stocks from 2004-02-06 to 2016-03-02.

Version:	0.1.0
Depends:	R (≥ 3.5.0)
Imports:	MASS, sparsevar
Suggests:	ggplot2
Published:	2025-01-09
DOI:	10.32614/CRAN.package.VARcpDetectOnline
Author:	Yuhan Tian [aut, cre], Abolfazl Safikhani [aut]
Maintainer:	Yuhan Tian <yuhan.tian at ufl.edu>
BugReports:	https://github.com/Helloworld9293/VARcpDetectOnline/issues
License:	MIT + file LICENSE
URL:	https://github.com/Helloworld9293/VARcpDetectOnline
NeedsCompilation:	no
CRAN checks:	VARcpDetectOnline results

Documentation:

Reference manual:

VARcpDetectOnline.pdf

Downloads:

Package source:	VARcpDetectOnline_0.1.0.tar.gz
Windows binaries:	r-devel: VARcpDetectOnline_0.1.0.zip, r-release: VARcpDetectOnline_0.1.0.zip, r-oldrel: VARcpDetectOnline_0.1.0.zip
macOS binaries:	r-release (arm64): VARcpDetectOnline_0.1.0.tgz, r-oldrel (arm64): VARcpDetectOnline_0.1.0.tgz, r-release (x86_64): VARcpDetectOnline_0.1.0.tgz, r-oldrel (x86_64): VARcpDetectOnline_0.1.0.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=VARcpDetectOnline to link to this page.