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VARcpDetectOnline  

Sequential Change Point Detection for High-Dimensional VAR Models
View on CRAN: Click here


Download and install VARcpDetectOnline package within the R console
Install from CRAN:
install.packages("VARcpDetectOnline")

Install from Github:
library("remotes")
install_github("cran/VARcpDetectOnline")

Install by package version:
library("remotes")
install_version("VARcpDetectOnline", "0.2.0")



Attach the package and use:
library("VARcpDetectOnline")
Maintained by
Yuhan Tian
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2025-01-09
Latest Update: 2025-02-13
Description:
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.
How to cite:
Yuhan Tian (2025). VARcpDetectOnline: Sequential Change Point Detection for High-Dimensional VAR Models. R package version 0.2.0, https://cran.r-project.org/web/packages/VARcpDetectOnline. Accessed 28 Jul. 2026.
Previous versions and publish date:
(2026-07-09 08:28), 0.1.0 (2025-01-09 15:10), 0.2.0 (2025-02-13 09:40)
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Complete documentation for VARcpDetectOnline
Functions, R codes and Examples using the VARcpDetectOnline R package
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