decomposedPSF: Time Series Prediction with PSF and Decomposition Methods (EMD and EEMD)

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>
License: GPL-2 | GPL-3 [expanded from: GPL]
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:, r-release:, r-oldrel:
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 dependencies:

Reverse imports: ForecastTB


Please use the canonical form to link to this page.