fnets: Factor-Adjusted Network Estimation and Forecasting for High-Dimensional Time Series

Implements methods for network estimation and forecasting of high-dimensional time series exhibiting strong serial and cross-sectional correlations under a factor-adjusted vector autoregressive model. See Barigozzi, Cho and Owens (2024+) <doi:10.1080/07350015.2023.2257270> for further descriptions of FNETS methodology and Owens, Cho and Barigozzi (2024+) <arXiv:2301.11675> accompanying the R package.

Version: 0.1.6
Depends: R (≥ 4.1.0)
Imports: lpSolve, parallel, doParallel, foreach, MASS, fields, igraph, RColorBrewer
Suggests: testthat (≥ 3.0.0)
Published: 2024-01-23
Author: Matteo Barigozzi [aut], Haeran Cho [cre, aut], Dom Owens [aut]
Maintainer: Haeran Cho <haeran.cho at bristol.ac.uk>
License: GPL (≥ 3)
NeedsCompilation: no
Materials: README
In views: TimeSeries
CRAN checks: fnets results

Documentation:

Reference manual: fnets.pdf

Downloads:

Package source: fnets_0.1.6.tar.gz
Windows binaries: r-devel: fnets_0.1.6.zip, r-release: fnets_0.1.6.zip, r-oldrel: fnets_0.1.6.zip
macOS binaries: r-release (arm64): fnets_0.1.6.tgz, r-oldrel (arm64): fnets_0.1.6.tgz, r-release (x86_64): fnets_0.1.6.tgz
Old sources: fnets archive

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