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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>.

Version: 1.1.2
Depends: R (≥ 3.5.0), methods, lattice
Imports: MASS, zoo, Rcpp, stats, utils, grDevices, graphics, abind
LinkingTo: Rcpp, RcppArmadillo, RcppEigen
Suggests: knitr, rmarkdown, gridExtra, expm, MCS, quantmod, codetools
Published: 2023-01-09
Author: Will Nicholson [cre, aut], David Matteson [aut], Jacob Bien [aut], Ines Wilms [aut]
Maintainer: Will Nicholson <wbn8 at cornell.edu>
BugReports: https://github.com/wbnicholson/BigVAR/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/wbnicholson/BigVAR
NeedsCompilation: yes
SystemRequirements: C++11
Materials: NEWS
In views: TimeSeries
CRAN checks: BigVAR results

Documentation:

Reference manual: BigVAR.pdf
Vignettes: BigVAR: Tools for Modeling Sparse Vector Autoregressions with Exogenous Variables

Downloads:

Package source: BigVAR_1.1.2.tar.gz
Windows binaries: r-devel: BigVAR_1.1.2.zip, r-release: BigVAR_1.1.2.zip, r-oldrel: BigVAR_1.1.2.zip
macOS binaries: r-release (arm64): BigVAR_1.1.2.tgz, r-oldrel (arm64): BigVAR_1.1.2.tgz, r-release (x86_64): BigVAR_1.1.2.tgz, r-oldrel (x86_64): BigVAR_1.1.2.tgz
Old sources: BigVAR archive

Reverse dependencies:

Reverse imports: VIRF
Reverse suggests: frequencyConnectedness

Linking:

Please use the canonical form https://CRAN.R-project.org/package=BigVAR to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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