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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.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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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.