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cff-version: 1.2.0
message: 'To cite package "VARcpDetectOnline" in publications use:'
type: software
license: MIT
title: 'VARcpDetectOnline: Sequential Change Point Detection for High-Dimensional
  VAR Models'
version: 0.1.0
doi: 10.32614/CRAN.package.VARcpDetectOnline
abstract: 'Implements the algorithm introduced in Tian, Y., and Safikhani, A. (2024)
  <https://doi.org/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.'
authors:
- family-names: Tian
  given-names: Yuhan
  email: yuhan.tian@ufl.edu
- family-names: Safikhani
  given-names: Abolfazl
  email: asafikha@gmu.edu
repository: https://helloworld9293.r-universe.dev
repository-code: https://github.com/Helloworld9293/VARcpDetectOnline
commit: db0f21dc0bfbcc0db8d8a150f180c812412afe1c
url: https://github.com/Helloworld9293/VARcpDetectOnline
contact:
- family-names: Tian
  given-names: Yuhan
  email: yuhan.tian@ufl.edu