robets: Forecasting Time Series with Robust Exponential Smoothing

We provide an outlier robust alternative of the function ets() in the 'forecast' package of Hyndman and Khandakar (2008) <doi:10.18637/jss.v027.i03>. For each method of a class of exponential smoothing variants we made a robust alternative. The class includes methods with a damped trend and/or seasonal components. The robust method is developed by robustifying every aspect of the original exponential smoothing variant. We provide robust forecasting equations, robust initial values, robust smoothing parameter estimation and a robust information criterion. The method is described in more detail in Crevits and Croux (2016) <doi:10.13140/RG.2.2.11791.18080>.

Version: 1.4
Depends: R (≥ 3.1.1)
Imports: Rcpp (≥ 0.12.2), forecast
LinkingTo: Rcpp
Published: 2018-03-06
Author: Ruben Crevits [aut, cre], Christoph Bergmeir [aut], Rob Hyndman [aut], Ross Ihaka [ctb], R Core Team [ctb]
Maintainer: Ruben Crevits <ruben.crevits at gmail.com>
BugReports: https://github.com/RubenCrevits/robets/issues
License: GPL-3
URL: http://github.com/RubenCrevits/robets
NeedsCompilation: yes
In views: TimeSeries
CRAN checks: robets results

Downloads:

Reference manual: robets.pdf
Package source: robets_1.4.tar.gz
Windows binaries: r-devel: robets_1.4.zip, r-devel-gcc8: robets_1.4.zip, r-release: robets_1.4.zip, r-oldrel: robets_1.4.zip
OS X binaries: r-release: robets_1.4.tgz, r-oldrel: robets_1.4.tgz
Old sources: robets archive

Reverse dependencies:

Reverse imports: sutteForecastR
Reverse suggests: sweep, timetk

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