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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+) <doi:10.48550/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 |
| Reference manual: | fnets.pdf |
| 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, r-oldrel (x86_64): fnets_0.1.6.tgz |
| Old sources: | fnets archive |
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