EEMDlstm: EEMD Based LSTM Model for Time Series Forecasting

Forecasting univariate time series with ensemble empirical mode decomposition (EEMD) with long short-term memory (LSTM). For method details see Jaiswal, R. et al. (2022). <doi:10.1007/s00521-021-06621-3>.

Version:	1.0.1
Depends:	R (≥ 2.10)
Imports:	keras, tensorflow, reticulate, tsutils, BiocGenerics, utils, graphics, magrittr, Rlibeemd, TSdeeplearning
Published:	2026-04-13
DOI:	10.32614/CRAN.package.EEMDlstm
Author:	Kapil Choudhary [aut], Girish Kumar Jha [aut, ths, ctb], Ronit Jaiswal [ctb, cre], Rajeev Ranjan Kumar [ctb]
Maintainer:	Ronit Jaiswal <ronitjaiswal2912 at gmail.com>
License:	GPL-3
NeedsCompilation:	no
CRAN checks:	EEMDlstm results

Documentation:

Reference manual:

EEMDlstm.html , EEMDlstm.pdf

Downloads:

Package source:	EEMDlstm_1.0.1.tar.gz
Windows binaries:	r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries:	r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): not available, r-oldrel (x86_64): not available
Old sources:	EEMDlstm archive

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