Enhanced Seasonal Decomposition of Time Series by Loess

Decompose a time series into seasonal, trend, and remainder components using an implementation of Seasonal Decomposition of Time Series by Loess (STL) that provides several enhancements over the STL method in the stats package. These enhancements include handling missing values, providing higher order (quadratic) loess smoothing with automated parameter choices, frequency component smoothing beyond the seasonal and trend components, and some basic plot methods for diagnostics.


Build Status

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This package contains enhancements to the Seasonal Trend Decomposition using Loess (STL) implementation that comes with base R, stl().

Here are some of the added features over stl():

  • Can handle NA values
  • Higher order loess smoothing (more than just local constant and linear)
  • Automated parameter choices for local quadratic
  • Frequency component smoothing beyond seasonal and trend
  • Plot methods for diagnostics

For (very) experimental inference, prediction, and variance reduction at endpoints, see the operator package.

References

Installation

devtools::install_github("hafen/stlplus")

License

This software is released under the BSD license. Please read the license document.

News

Reference manual

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install.packages("stlplus")

0.5.1 by Ryan Hafen, 3 years ago


https://github.com/hafen/stlplus


Report a bug at https://github.com/hafen/stlplus/issues


Browse source code at https://github.com/cran/stlplus


Authors: Ryan Hafen [aut, cre]


Documentation:   PDF Manual  


Task views: Time Series Analysis, Missing Data


BSD_3_clause + file LICENSE license


Imports lattice, yaImpute, stats, Rcpp

Suggests testthat

Linking to Rcpp


Imported by KarsTS.


See at CRAN