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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 |
| Reference manual: | EEMDlstm.html , EEMDlstm.pdf |
| Package source: | EEMDlstm_1.0.1.tar.gz |
| Windows binaries: | r-devel: not available, r-release: EEMDlstm_1.0.1.zip, r-oldrel: not available |
| macOS binaries: | r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): EEMDlstm_1.0.1.tgz, r-oldrel (x86_64): EEMDlstm_1.0.1.tgz |
| Old sources: | EEMDlstm archive |
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These binaries (installable software) and packages are in development.
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