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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: | 0.6 |
| Depends: | R (≥ 3.5.0) |
| Imports: | compiler, Matrix, SparseM, quantreg, forecast, foreach, stats, methods, graphics, grDevices |
| Suggests: | testthat, demography, knitr, rmarkdown, doParallel, seasonal, rgl |
| Published: | 2023-08-10 |
| Author: | Alexander Dokumentov, Rob J Hyndman |
| Maintainer: | Alexander Dokumentov <alexander.dokumentov at gmail.com> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: | https://bitbucket.org/alexanderdokumentov/strpackage |
| NeedsCompilation: | no |
| Materials: | ChangeLog |
| In views: | TimeSeries |
| CRAN checks: | stR results |
| Reference manual: | stR.pdf |
| Vignettes: |
Package stR |
| Package source: | stR_0.6.tar.gz |
| Windows binaries: | r-devel: stR_0.6.zip, r-release: stR_0.6.zip, r-oldrel: stR_0.6.zip |
| macOS binaries: | r-release (arm64): stR_0.6.tgz, r-oldrel (arm64): stR_0.6.tgz, r-release (x86_64): stR_0.6.tgz, r-oldrel (x86_64): stR_0.6.tgz |
| Old sources: | stR archive |
| Reverse imports: | ATAforecasting |
| Reverse suggests: | dsa |
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