Package: VARcpDetectOnline 0.2.1
Yuhan Tian
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 VAR models, effectively identifying shifts in temporal and cross-correlations within high-dimensional time series data.
Authors:
VARcpDetectOnline_0.2.1.tar.gz
VARcpDetectOnline_0.2.1.tar.gz(r-4.7-any)VARcpDetectOnline_0.2.1.tar.gz(r-4.6-any)
VARcpDetectOnline_0.2.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
VARcpDetectOnline/json (API)
| # Install 'VARcpDetectOnline' in R: |
| install.packages('VARcpDetectOnline', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/helloworld9293/varcpdetectonline/issues
- sp500 - S&P 500 Daily Log Returns and Corresponding Dates
Last updated from:8cacd0fdd3. Checks:4 OK. Indexed: no.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 115 | ||
| source / vignettes | OK | 189 | ||
| linux-release-x86_64 | OK | 138 | ||
| wasm-release | OK | 135 |
Exports:fitVARgenerateVARget_cpsVAR_cpDetect_Online
Dependencies:codetoolscorpcordoParallelforeachglmnetiteratorslatticeMASSMatrixRcppRcppEigenshapesurvival
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Fit VAR Model with Elastic Net via Cross Validation | fitVAR |
| Generate VAR Data | generateVAR |
| Identify the Beginning of the Alarm Clusters | get_cps |
| S&P 500 Daily Log Returns and Corresponding Dates | sp500 |
| VAR_cpDetect_Online: Sequential change point Detection for Vector Auto-Regressive Models | VAR_cpDetect_Online |
