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: 0.1.3
Imports: PSF, Rlibeemd, forecast, tseries
Suggests: knitr, rmarkdown
Published: 2017-07-09
Author: Neeraj Bokde
Maintainer: Neeraj Bokde <neerajdhanraj at>
License: GPL-2 | GPL-3 [expanded from: GPL]
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:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): decomposedPSF_0.1.3.tgz, r-release (x86_64): decomposedPSF_0.1.3.tgz, r-oldrel: decomposedPSF_0.1.3.tgz

Reverse dependencies:

Reverse imports: ForecastTB


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