nnfor: Time Series Forecasting with Neural Networks

Automatic time series modelling with neural networks. Allows fully automatic, semi-manual or fully manual specification of networks. For details of the specification methodology see: (i) Crone and Kourentzes (2010) <doi:10.1016/j.neucom.2010.01.017>; and (ii) Kourentzes et al. (2014) <doi:10.1016/j.eswa.2013.12.011>.

Version: 0.9.9
Depends: generics
Imports: forecast, glmnet, neuralnet, plotrix, MASS, tsutils, uroot, methods
Suggests: thief
Published: 2023-11-15
DOI: 10.32614/CRAN.package.nnfor
Author: Nikolaos Kourentzes [aut, cre]
Maintainer: Nikolaos Kourentzes <nikolaos at kourentzes.com>
BugReports: https://github.com/trnnick/nnfor/issues
License: GPL-3
URL: https://kourentzes.com/forecasting/2019/01/16/tutorial-for-the-nnfor-r-package/
NeedsCompilation: no
Materials: README NEWS
In views: TimeSeries
CRAN checks: nnfor results


Reference manual: nnfor.pdf


Package source: nnfor_0.9.9.tar.gz
Windows binaries: r-devel: nnfor_0.9.9.zip, r-release: nnfor_0.9.9.zip, r-oldrel: nnfor_0.9.9.zip
macOS binaries: r-release (arm64): nnfor_0.9.9.tgz, r-oldrel (arm64): nnfor_0.9.9.tgz, r-release (x86_64): nnfor_0.9.9.tgz, r-oldrel (x86_64): nnfor_0.9.9.tgz
Old sources: nnfor archive

Reverse dependencies:

Reverse imports: EEMDelm, hybridts, mrf, MSGARCHelm, stlELM, stlTDNN, tswge, VMDML, vmdTDNN


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