VMDML: Variational Mode Decomposition Based Machine Learning Models

Application of Variational Mode Decomposition based different Machine Learning models for univariate time series forecasting. For method details see (i) K. Dragomiretskiy and D. Zosso (2014) <doi:10.1109/TSP.2013.2288675>; (ii) Pankaj Das (2020) <http://krishi.icar.gov.in/jspui/handle/123456789/44138>.

Version:	0.1.1
Imports:	VMDecomp, forecast, e1071, randomForest, nnfor
Suggests:	knitr, rmarkdown, testthat (≥ 3.0.0)
Published:	2023-08-27
DOI:	10.32614/CRAN.package.VMDML
Author:	Pankaj Das [aut, cre], Girish Kumar Jha [aut], Tauqueer Ahmad [aut], Achal Lama [aut], Lampros Mouselimis [cph]
Maintainer:	Pankaj Das <pankaj.das2 at icar.gov.in>
License:	MIT + file LICENSE
NeedsCompilation:	no
CRAN checks:	VMDML results

Documentation:

Reference manual:	VMDML.pdf
Vignettes:	VMDML

Downloads:

Package source:	VMDML_0.1.1.tar.gz
Windows binaries:	r-devel: VMDML_0.1.1.zip, r-release: VMDML_0.1.1.zip, r-oldrel: VMDML_0.1.1.zip
macOS binaries:	r-release (arm64): VMDML_0.1.1.tgz, r-oldrel (arm64): VMDML_0.1.1.tgz, r-release (x86_64): VMDML_0.1.1.tgz, r-oldrel (x86_64): VMDML_0.1.1.tgz
Old sources:	VMDML archive

Linking:

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