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NetVAR: Network Structures in VAR Models

Vector AutoRegressive (VAR) type models with tailored regularisation structures are provided to uncover network type structures in the data, such as influential time series (influencers). Currently the package implements the LISAR model from Zhang and Trimborn (2023) <doi:10.2139/ssrn.4619531>. The package automatically derives the required regularisation sequences and refines it during the estimation to provide the optimal model. The package allows for model optimisation under various loss functions such as Mean Squared Forecasting Error (MSFE), Akaike Information Criterion (AIC), and Bayesian Information Criterion (BIC). It provides a dedicated class, allowing for summary prints of the optimal model and a plotting function to conveniently analyse the optimal model via heatmaps.

Version: 0.1-2
Depends: R (≥ 3.5.0)
Imports: fields, fGarch
Published: 2025-09-22
DOI: 10.32614/CRAN.package.NetVAR
Author: Simon Trimborn [aut, cre]
Maintainer: Simon Trimborn <trimborn.econometrics at gmail.com>
License: GPL (≥ 3)
NeedsCompilation: yes
Citation: NetVAR citation info
In views: TimeSeries
CRAN checks: NetVAR results

Documentation:

Reference manual: NetVAR.html , NetVAR.pdf

Downloads:

Package source: NetVAR_0.1-2.tar.gz
Windows binaries: r-devel: NetVAR_0.1-2.zip, r-release: NetVAR_0.1-2.zip, r-oldrel: NetVAR_0.1-2.zip
macOS binaries: r-release (arm64): NetVAR_0.1-2.tgz, r-oldrel (arm64): NetVAR_0.1-2.tgz, r-release (x86_64): NetVAR_0.1-2.tgz, r-oldrel (x86_64): NetVAR_0.1-2.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=NetVAR 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.