Functions for time series preprocessing, decomposition, prediction and accuracy assessment using automatic linear modelling. The generated linear models and its yielded prediction errors can be used for benchmarking other time series prediction methods and for creating a demand for the refinement of such methods. For this purpose, benchmark data from prediction competitions may be used.
| Version: | 4.0 |
| Depends: | R (≥ 2.10) |
| Imports: | forecast, KFAS, stats, MuMIn, EMD, wavelets, vars |
| Published: | 2018-06-21 |
| Author: | Rebecca Pontes Salles [aut, cre, cph] (CEFET/RJ), Eduardo Ogasawara [ths] (CEFET/RJ) |
| Maintainer: | Rebecca Pontes Salles <rebeccapsalles at acm.org> |
| BugReports: | https://github.com/RebeccaSalles/TSPred/issues |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: | https://github.com/RebeccaSalles/TSPred/wiki |
| NeedsCompilation: | no |
| Citation: | TSPred citation info |
| CRAN checks: | TSPred results |
| Reference manual: | TSPred.pdf |
| Package source: | TSPred_4.0.tar.gz |
| Windows binaries: | r-devel: TSPred_4.0.zip, r-release: TSPred_4.0.zip, r-oldrel: TSPred_4.0.zip |
| macOS binaries: | r-release: TSPred_4.0.tgz, r-oldrel: TSPred_4.0.tgz |
| Old sources: | TSPred archive |
| Reverse imports: | predtoolsTS |
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