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.

Package details

AuthorAlexander Dokumentov [aut] (<https://orcid.org/0000-0003-0478-0983>), Rob Hyndman [aut, cre] (<https://orcid.org/0000-0002-2140-5352>)
MaintainerRob Hyndman <Rob.Hyndman@monash.edu>
LicenseGPL-3
Version0.7
URL https://pkg.robjhyndman.com/stR/ https://github.com/robjhyndman/stR
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("stR")

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stR documentation built on Sept. 11, 2024, 5:39 p.m.