Package: NetVAR 0.1-2

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.

Authors:Simon Trimborn [aut, cre]

NetVAR_0.1-2.tar.gz
NetVAR_0.1-2.zip(r-4.7)NetVAR_0.1-2.zip(r-4.6)NetVAR_0.1-2.zip(r-4.5)
NetVAR_0.1-2.tgz(r-4.6-any)NetVAR_0.1-2.tgz(r-4.5-any)
NetVAR_0.1-2.tar.gz(r-4.7-any)NetVAR_0.1-2.tar.gz(r-4.6-any)
NetVAR_0.1-2.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
NetVAR/json (API)

# Install 'NetVAR' in R:
install.packages('NetVAR', repos = c('https://simontrimborn.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/simontrimborn/netvar/issues

Datasets:
  • TradingData - Trading data for 11 US stocks from the finance sector

On CRAN:

Conda:

3.88 score 3 stars 179 downloads 1 exports 22 dependencies

Last updated from:13f003e686. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK168
source / vignettesOK135
linux-release-x86_64OK151
macos-release-arm64OK189
macos-oldrel-arm64OK164
windows-develOK102
windows-releaseOK101
windows-oldrelOK93
wasm-releaseOK99

Exports:LISAR

Dependencies:cvardotCall64fastICAfBasicsfGarchfieldsgbutilsgsslatticemapsMASSMatrixrbibutilsRColorBrewerRcppRdpackspamspatialstabledisttimeDatetimeSeriesviridisLite