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: | 0.1.3 |
| Imports: | PSF, Rlibeemd, forecast, tseries |
| Suggests: | knitr, rmarkdown |
| Published: | 2017-07-09 |
| Author: | Neeraj Bokde |
| Maintainer: | Neeraj Bokde <neerajdhanraj at gmail.com> |
| License: | GPL-2 | GPL-3 [expanded from: GPL] |
| URL: | http://www.neerajbokde.com/ |
| NeedsCompilation: | no |
| CRAN checks: | decomposedPSF results |
| Reference manual: | decomposedPSF.pdf |
| Vignettes: |
Vignette Title |
| Package source: | decomposedPSF_0.1.3.tar.gz |
| Windows binaries: | r-devel: decomposedPSF_0.1.3.zip, r-release: decomposedPSF_0.1.3.zip, r-oldrel: decomposedPSF_0.1.3.zip |
| macOS binaries: | r-release (arm64): decomposedPSF_0.1.3.tgz, r-oldrel (arm64): decomposedPSF_0.1.3.tgz, r-release (x86_64): decomposedPSF_0.1.3.tgz, r-oldrel (x86_64): decomposedPSF_0.1.3.tgz |
| Reverse imports: | ForecastTB |
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