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NVAR: Nonlinear Vector Autoregression Models

Estimate nonlinear vector autoregression models (also known as the next generation reservoir computing) for nonlinear dynamic systems. The algorithm was described by Gauthier et al. (2021) <doi:10.1038/s41467-021-25801-2>.

Version: 0.1.0
Imports: dplyr, magrittr, purrr, rlang, stats, tibble, tidyr
Suggests: ggplot2, nonlinearTseries, testthat (≥ 3.0.0)
Published: 2024-01-18
DOI: 10.32614/CRAN.package.NVAR
Author: Jingmeng Cui ORCID iD [aut, cre]
Maintainer: Jingmeng Cui <jingmeng.cui at outlook.com>
BugReports: https://github.com/Sciurus365/NVAR/issues
License: GPL (≥ 3)
URL: https://github.com/Sciurus365/NVAR
NeedsCompilation: no
Materials: README NEWS
In views: TimeSeries
CRAN checks: NVAR results

Documentation:

Reference manual: NVAR.pdf

Downloads:

Package source: NVAR_0.1.0.tar.gz
Windows binaries: r-devel: NVAR_0.1.0.zip, r-release: NVAR_0.1.0.zip, r-oldrel: NVAR_0.1.0.zip
macOS binaries: r-release (arm64): NVAR_0.1.0.tgz, r-oldrel (arm64): NVAR_0.1.0.tgz, r-release (x86_64): NVAR_0.1.0.tgz, r-oldrel (x86_64): NVAR_0.1.0.tgz

Linking:

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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.