stR: Seasonal Trend Decomposition Using Regression

Methods for decomposing seasonal data: STR (a Seasonal-Trend time series 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 also be used for forecasting.

Version:	0.7
Depends:	R (≥ 3.5.0)
Imports:	compiler, foreach, forecast, graphics, grDevices, Matrix, methods, quantreg, SparseM, stats
Suggests:	demography, doParallel, knitr, markdown, rgl, rmarkdown, seasonal, testthat
Published:	2024-07-28
DOI:	10.32614/CRAN.package.stR
Author:	Alexander Dokumentov [aut], Rob Hyndman [aut, cre]
Maintainer:	Rob Hyndman <Rob.Hyndman at monash.edu>
BugReports:	https://github.com/robjhyndman/stR/issues
License:	GPL-3
URL:	https://pkg.robjhyndman.com/stR/, https://github.com/robjhyndman/stR
NeedsCompilation:	no
Citation:	stR citation info
Materials:	README NEWS
In views:	TimeSeries
CRAN checks:	stR results

Documentation:

Reference manual:	stR.pdf
Vignettes:	Package stR

Downloads:

Package source:	stR_0.7.tar.gz
Windows binaries:	r-devel: stR_0.7.zip, r-release: stR_0.7.zip, r-oldrel: stR_0.7.zip
macOS binaries:	r-release (arm64): stR_0.7.tgz, r-oldrel (arm64): stR_0.7.tgz, r-release (x86_64): stR_0.7.tgz, r-oldrel (x86_64): stR_0.7.tgz
Old sources:	stR archive

Reverse dependencies:

Reverse imports:	ATAforecasting
Reverse suggests:	dsa

Linking:

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