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: |
0.10.0 |
| Depends: |
generics |
| Imports: |
forecast, glmnet, neuralnet, plotrix, MASS, tsutils (≥
0.9.5), uroot, parallel, datasets |
| Suggests: |
thief, torch, testthat (≥ 3.0.0) |
| Published: |
2026-11-13 |
| 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 |
Documentation:
Downloads:
Reverse dependencies:
| Reverse imports: |
decompML, EEMDelm, hybridts, mrf, MSGARCHelm, Saylac, stlELM, stlTDNN, tswge, VMDML, vmdTDNN |
| Reverse suggests: |
mlr3forecast |
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