Predict future values with hybrid combinations of Pattern Sequence based Forecasting (PSF), Autoregressive Integrated Moving Average (ARIMA), Empirical Mode Decomposition (EMD) and Ensemble Empirical Mode Decomposition (EEMD) methods based hybrid methods.
| Version: | 0.2 |
| Imports: | PSF, Rlibeemd, forecast, tseries |
| Suggests: | knitr, rmarkdown |
| Published: | 2022-05-01 |
| DOI: | 10.32614/CRAN.package.decomposedPSF |
| Author: | Neeraj Bokde |
| Maintainer: | Neeraj Bokde <neerajdhanraj at gmail.com> |
| License: | GPL-2 | GPL-3 [expanded from: GPL] |
| URL: | https://www.neerajbokde.in/software/ |
| NeedsCompilation: | no |
| Citation: | decomposedPSF citation info |
| CRAN checks: | decomposedPSF results |
| Reference manual: | decomposedPSF.pdf |
| Vignettes: |
decomposedPSF-vignette |
| Package source: | decomposedPSF_0.2.tar.gz |
| Windows binaries: | r-devel: decomposedPSF_0.2.zip, r-release: decomposedPSF_0.2.zip, r-oldrel: decomposedPSF_0.2.zip |
| macOS binaries: | r-release (arm64): decomposedPSF_0.2.tgz, r-oldrel (arm64): decomposedPSF_0.2.tgz, r-release (x86_64): decomposedPSF_0.2.tgz, r-oldrel (x86_64): decomposedPSF_0.2.tgz |
| Old sources: | decomposedPSF archive |
| Reverse imports: | ForecastTB |
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