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
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

Documentation:

Reference manual: decomposedPSF.pdf
Vignettes: decomposedPSF-vignette

Downloads:

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 dependencies:

Reverse imports: ForecastTB

Linking:

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