washeR: Time Series Outlier Detection

Time series outlier detection with non parametric test. This is a new outlier detection methodology (washer): efficient for time saving elaboration and implementation procedures, adaptable for general assumptions and for needing very short time series, reliable and effective as involving robust non parametric test. You can find two approaches: single time series (a vector) and grouped time series (a data frame). For other informations: Andrea Venturini (2011) Statistica - Universita di Bologna, Vol.71, pp.329-344. For an informal explanation look at R-bloggers on web.

Version: 0.1.3
Imports: gplots, grDevices, graphics, stats, utils
Published: 2022-09-20
Author: Andrea Venturini
Maintainer: Andrea Venturini <andrea.venturini at bancaditalia.it>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: washeR results


Reference manual: washeR.pdf


Package source: washeR_0.1.3.tar.gz
Windows binaries: r-devel: washeR_0.1.3.zip, r-release: washeR_0.1.3.zip, r-oldrel: washeR_0.1.3.zip
macOS binaries: r-release (arm64): washeR_0.1.3.tgz, r-oldrel (arm64): washeR_0.1.3.tgz, r-release (x86_64): washeR_0.1.3.tgz, r-oldrel (x86_64): washeR_0.1.3.tgz
Old sources: washeR archive


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