EMDANNhybrid: Empirical Mode Decomposition Based Artificial Neural Network Model

Application of empirical mode decomposition based artificial neural network model for nonlinear and non stationary univariate time series forecasting. For method details see (i) Choudhury (2019) <https://www.indianjournals.com/ijor.aspx?target=ijor:ijee3&volume=55&issue=1&article=013>; (ii) Das (2020) <https://www.indianjournals.com/ijor.aspx?target=ijor:ijee3&volume=56&issue=2&article=002>.

Version: 0.2.0
Depends: EMD, forecast
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2023-09-14
DOI: NA
Author: Pankaj Das ORCID iD [aut, cre], Achal Lama [aut], Girish Kumar Jha [aut]
Maintainer: Pankaj Das <pankaj.das2 at icar.gov.in>
License: GPL-3
NeedsCompilation: no
CRAN checks: EMDANNhybrid results

Documentation:

Reference manual: EMDANNhybrid.pdf
Vignettes: EMDANNhybrid

Downloads:

Package source: EMDANNhybrid_0.2.0.tar.gz
Windows binaries: r-devel: EMDANNhybrid_0.2.0.zip, r-release: EMDANNhybrid_0.2.0.zip, r-oldrel: EMDANNhybrid_0.2.0.zip
macOS binaries: r-release (arm64): EMDANNhybrid_0.2.0.tgz, r-oldrel (arm64): EMDANNhybrid_0.2.0.tgz, r-release (x86_64): EMDANNhybrid_0.2.0.tgz, r-oldrel (x86_64): EMDANNhybrid_0.2.0.tgz
Old sources: EMDANNhybrid archive

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