tsintermittent: Intermittent Time Series Forecasting

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
Author: Nikolaos Kourentzes ORCID iD [cre, aut], Fotios Petropoulos ORCID iD [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

Documentation:

Reference manual: tsintermittent.pdf

Downloads:

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
Old sources: tsintermittent archive

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