High-Performance Open-Source Archive
Univariate time series forecasting with STL decomposition based Extreme Learning Machine hybrid model. For method details see Xiong T, Li C, Bao Y (2018). <doi:10.1016/j.neucom.2017.11.053>.
| Version: | 0.1.1 |
| Depends: | R (≥ 2.10) |
| Imports: | forecast, nnfor |
| Published: | 2022-08-09 |
| DOI: | 10.32614/CRAN.package.stlELM |
| Author: | Girish Kumar Jha [aut, cre], Ronit Jaiswal [aut, ctb], Kapil Choudhary [ctb], Rajeev Ranjan Kumar [ctb] |
| Maintainer: | Girish Kumar Jha <girish.stat at gmail.com> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| In views: | Agriculture |
| CRAN checks: | stlELM results |
| Reference manual: | stlELM.html , stlELM.pdf |
| Package source: | stlELM_0.1.1.tar.gz |
| Windows binaries: | r-devel: stlELM_0.1.1.zip, r-release: stlELM_0.1.1.zip, r-oldrel: stlELM_0.1.1.zip |
| macOS binaries: | r-release (arm64): stlELM_0.1.1.tgz, r-oldrel (arm64): stlELM_0.1.1.tgz, r-release (x86_64): stlELM_0.1.1.tgz, r-oldrel (x86_64): stlELM_0.1.1.tgz |
| Old sources: | stlELM archive |
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