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

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