Package: BigVAR 1.1.2
Will Nicholson
BigVAR: Dimension Reduction Methods for Multivariate Time Series
Estimates VAR and VARX models with Structured Penalties using the methods developed by Nicholson et al (2017)<doi:10.1016/j.ijforecast.2017.01.003> and Nicholson et al (2020) <doi:10.48550/arXiv.1412.5250>.
Authors:
BigVAR_1.1.2.tar.gz
BigVAR_1.1.2.tar.gz(r-4.5-noble)BigVAR_1.1.2.tar.gz(r-4.4-noble)
BigVAR_1.1.2.tgz(r-4.4-emscripten)BigVAR_1.1.2.tgz(r-4.3-emscripten)
BigVAR.pdf |BigVAR.html✨
BigVAR/json (API)
NEWS
| # Install 'BigVAR' in R: |
| install.packages('BigVAR', repos = 'https://cloud.r-project.org') |
Bug tracker:https://github.com/wbnicholson/bigvar/issues22 issues
Last updated 2 years agofrom:96d776b14e. Checks:1 OK, 2 NOTE. Indexed: no.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Mar 30 2025 |
| R-4.5-linux-x86_64 | NOTE | Mar 30 2025 |
| R-4.4-linux-x86_64 | NOTE | Mar 30 2025 |
Exports:BigVAR.estBigVAR.fitcoefconstructModelcv.BigVARMultVarSimplotpredictPredictVARXshowSparsityPlot.BigVAR.resultsVarptoVar1MCVARXFitVARXForecastEvalVARXLagCons
Citation
To cite package ‘BigVAR’ in publications use:
Nicholson W, Matteson D, Bien J, Wilms I (2023). BigVAR: Dimension Reduction Methods for Multivariate Time Series. R package version 1.1.2, https://CRAN.R-project.org/package=BigVAR.
Corresponding BibTeX entry:
@Manual{,
title = {BigVAR: Dimension Reduction Methods for Multivariate Time
Series},
author = {Will Nicholson and David Matteson and Jacob Bien and Ines
Wilms},
year = {2023},
note = {R package version 1.1.2},
url = {https://CRAN.R-project.org/package=BigVAR},
}