tsoutliers: Detection of Outliers in Time Series

Detection of outliers in time series following the Chen and Liu (1993) <doi:10.2307/2290724> procedure. Innovational outliers, additive outliers, level shifts, temporary changes and seasonal level shifts are considered.

Version: 0.6-8
Depends: R (≥ 3.0.0)
Imports: forecast, stats
Published: 2019-02-24
Author: Javier López-de-Lacalle
Maintainer: Javier López-de-Lacalle <javlacalle at yahoo.es>
License: GPL-2
URL: https://jalobe.com
NeedsCompilation: no
Materials: NEWS
In views: TimeSeries
CRAN checks: tsoutliers results

Documentation:

Reference manual: tsoutliers.pdf
Vignettes: tsoutliers-intro

Downloads:

Package source: tsoutliers_0.6-8.tar.gz
Windows binaries: r-devel: tsoutliers_0.6-8.zip, r-release: tsoutliers_0.6-8.zip, r-oldrel: tsoutliers_0.6-8.zip
macOS binaries: r-release (arm64): tsoutliers_0.6-8.tgz, r-oldrel (arm64): tsoutliers_0.6-8.tgz, r-release (x86_64): tsoutliers_0.6-8.tgz, r-oldrel (x86_64): tsoutliers_0.6-8.tgz
Old sources: tsoutliers archive

Reverse dependencies:

Reverse imports: composits, dsa

Linking:

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