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