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 [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

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, r-oldrel (x86_64): tsintermittent_1.10.tgz
Old sources:	tsintermittent archive

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