Package: stR 0.7.0.9000

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.

Authors:Alexander Dokumentov [aut], Rob Hyndman [aut, cre]

stR_0.7.0.9000.tar.gz
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stR.pdf |stR.html
stR/json (API)
NEWS

# Install 'stR' in R:
install.packages('stR', repos = c('https://robjhyndman.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/robjhyndman/str/issues

Pkgdown site:https://pkg.robjhyndman.com

Datasets:
  • calls - Number of phone calls dataset
  • electricity - Electricity consumption dataset
  • grocery - Grocery and supermarkets turnover

On CRAN:

Conda:

7.02 score 7 stars 2 packages 1.3k scripts 878 downloads 8 exports 52 dependencies

Last updated 1 months agofrom:37888ac68a. Checks:1 ERROR, 7 WARNING. Indexed: yes.

TargetResultLatest binary
Doc / VignettesFAILFeb 25 2025
R-4.5-winWARNINGFeb 25 2025
R-4.5-macWARNINGFeb 25 2025
R-4.5-linuxWARNINGFeb 25 2025
R-4.4-winWARNINGFeb 25 2025
R-4.4-macWARNINGFeb 25 2025
R-4.3-winWARNINGFeb 25 2025
R-4.3-macWARNINGFeb 25 2025

Exports:AutoSTRcomponentsheuristicSTRplotBetaRSTRmodelseasadjSTRSTRmodel

Dependencies:clicodetoolscolorspacecurlfansifarverforeachforecastfracdiffgenericsggplot2gluegtableisobanditeratorsjsonlitelabelinglatticelifecyclelmtestmagrittrMASSMatrixMatrixModelsmgcvmunsellnlmennetpillarpkgconfigquadprogquantmodquantregR6RColorBrewerRcppRcppArmadillorlangscalesSparseMsurvivaltibbletimeDatetseriesTTRurcautf8vctrsviridisLitewithrxtszoo