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Univariate time series forecasting with STL decomposition based auto regressive integrated moving average (ARIMA) hybrid model. For method details see Xiong T, Li C, Bao Y (2018). <doi:10.1016/j.neucom.2017.11.053>.
| Version: | 0.1.0 |
| Depends: | R (≥ 2.10) |
| Imports: | forecast |
| Published: | 2021-08-16 |
| DOI: | 10.32614/CRAN.package.stlARIMA |
| Author: | Ronit Jaiswal [aut, cre], Girish Kumar Jha [aut, ctb], Rajeev Ranjan Kumar [ctb], Kapil Choudhary [ctb] |
| Maintainer: | Ronit Jaiswal <ronitjaiswal2912 at gmail.com> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| CRAN checks: | stlARIMA results |
| Reference manual: | stlARIMA.pdf |
| Package source: | stlARIMA_0.1.0.tar.gz |
| Windows binaries: | r-devel: stlARIMA_0.1.0.zip, r-release: stlARIMA_0.1.0.zip, r-oldrel: stlARIMA_0.1.0.zip |
| macOS binaries: | r-release (arm64): stlARIMA_0.1.0.tgz, r-oldrel (arm64): stlARIMA_0.1.0.tgz, r-release (x86_64): stlARIMA_0.1.0.tgz, r-oldrel (x86_64): stlARIMA_0.1.0.tgz |
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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.