smooth: Forecasting Using Smoothing Functions

The set of smoothing functions used for time series analysis and in forecasting. Currently the package includes exponential smoothing models and SARIMA in state-space form + several simulation functions.

Version: 1.4.5
Depends: R (≥ 3.0.2)
Imports: Rcpp (≥ 0.12.3), stats, graphics, zoo, nloptr, utils
LinkingTo: Rcpp, RcppArmadillo (≥ 0.6.500.0.0)
Suggests: Mcomp, forecast, numDeriv, testthat, knitr, rmarkdown
Published: 2016-10-17
Author: Ivan Svetunkov [aut, cre] (Research Associate at Lancaster Centre for Forecasting, UK)
Maintainer: Ivan Svetunkov <ivan at svetunkov.ru>
BugReports: https://github.com/config-i1/smooth/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/config-i1/smooth
NeedsCompilation: yes
Materials: README NEWS
In views: TimeSeries
CRAN checks: smooth results

Downloads:

Reference manual: smooth.pdf
Vignettes: ces() - Complex Exponential Smoothing
es() - Exponential Smoothing
ges() - Generalised Exponential Smoothing
simulate(), sim.es() - simulate exponential smoothing
sma() - Simple Moving Average
smooth
ssarima() - State-Space ARIMA
Package source: smooth_1.4.5.tar.gz
Windows binaries: r-devel: smooth_1.4.5.zip, r-release: smooth_1.4.5.zip, r-oldrel: smooth_1.4.5.zip
OS X Mavericks binaries: r-release: smooth_1.4.5.tgz, r-oldrel: smooth_1.4.5.tgz
Old sources: smooth archive

Linking:

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