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: 0.1.0
Depends: R (≥ 2.10)
Imports: keras, tensorflow, reticulate, tsutils, BiocGenerics, utils, graphics, magrittr, Rlibeemd, TSdeeplearning
Published: 2022-09-26
Author: Kapil Choudhary [aut, cre], Girish Kumar Jha [aut, ths, ctb], Ronit Jaiswal [ctb], Rajeev Ranjan Kumar [ctb]
Maintainer: Kapil Choudhary <kapiliasri at>
License: GPL-3
NeedsCompilation: no
CRAN checks: EEMDlstm results


Reference manual: EEMDlstm.pdf


Package source: EEMDlstm_0.1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): EEMDlstm_0.1.0.tgz, r-oldrel (arm64): EEMDlstm_0.1.0.tgz, r-release (x86_64): EEMDlstm_0.1.0.tgz, r-oldrel (x86_64): EEMDlstm_0.1.0.tgz


Please use the canonical form to link to this page.