Time series methods for intermittent demand forecasting. Includes Croston's method and its variants (Moving Average, SBA), and the TSB method. Users can obtain optimal parameters on a variety of loss functions, or use fixed ones (Kourenztes (2014) <doi:10.1016/j.ijpe.2014.06.007>). Intermittent time series classification methods and iMAPA that uses multiple temporal aggregation levels are also provided (Petropoulos & Kourenztes (2015) <doi:10.1057/jors.2014.62>).
Version: | 1.10 |
Imports: | MAPA, parallel |
Published: | 2022-07-18 |
DOI: | 10.32614/CRAN.package.tsintermittent |
Author: | Nikolaos Kourentzes [cre, aut], Fotios Petropoulos [ctb] |
Maintainer: | Nikolaos Kourentzes <nikolaos at kourentzes.com> |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
URL: | https://kourentzes.com/forecasting/2014/06/23/intermittent-demand-forecasting-package-for-r/ |
NeedsCompilation: | no |
Materials: | README ChangeLog |
In views: | TimeSeries |
CRAN checks: | tsintermittent results |
Reference manual: | tsintermittent.pdf |
Package source: | tsintermittent_1.10.tar.gz |
Windows binaries: | r-devel: tsintermittent_1.10.zip, r-release: tsintermittent_1.10.zip, r-oldrel: tsintermittent_1.10.zip |
macOS binaries: | r-release (arm64): tsintermittent_1.10.tgz, r-oldrel (arm64): tsintermittent_1.10.tgz, r-release (x86_64): tsintermittent_1.10.tgz, r-oldrel (x86_64): tsintermittent_1.10.tgz |
Old sources: | tsintermittent archive |
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