stR: STR Decomposition

Methods for decomposing seasonal data: STR (a Seasonal-Trend decomposition procedure based on Regression) and Robust STR. In some ways, STR is similar to Ridge Regression and Robust STR can be related to LASSO. They allow for multiple seasonal components, multiple linear covariates with constant, flexible and seasonal influence. Seasonal patterns (for both seasonal components and seasonal covariates) can be fractional and flexible over time; moreover they can be either strictly periodic or have a more complex topology. The methods provide confidence intervals for the estimated components. The methods can be used for forecasting.

Version: 0.3
Depends: R (≥ 3.2.2)
Imports: compiler, Matrix, SparseM, quantreg, forecast, foreach, stats, methods, graphics, grDevices, rgl
Suggests: testthat, demography, knitr, rmarkdown, doParallel, doMC, seasonal
Published: 2017-01-06
Author: Alexander Dokumentov, Rob J Hyndman
Maintainer: Alexander Dokumentov <alexander.dokumentov at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Materials: ChangeLog
In views: TimeSeries
CRAN checks: stR results


Reference manual: stR.pdf
Vignettes: Package stR
Package source: stR_0.3.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X El Capitan binaries: r-release: stR_0.3.tgz
OS X Mavericks binaries: r-oldrel: stR_0.3.tgz
Old sources: stR archive


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