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StructuralDecompose: Decomposes a Level Shifted Time Series

Explains the behavior of a time series by decomposing it into its trend, seasonality and residuals. It is built to perform very well in the presence of significant level shifts. It is designed to play well with any breakpoint algorithm and any smoothing algorithm. Currently defaults to 'lowess' for smoothing and 'strucchange' for breakpoint identification. The package is useful in areas such as trend analysis, time series decomposition, breakpoint identification and anomaly detection.

Version: 0.1.1
Depends: R (≥ 2.10)
Imports: changepoint, segmented, strucchange
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2023-02-13
DOI: 10.32614/CRAN.package.StructuralDecompose
Author: Allen Sunny [aut, cre]
Maintainer: Allen Sunny <allensunny1242 at gmail.com>
License: MIT + file LICENSE
URL: https://allen-1242.github.io/StructuralDecompose/
NeedsCompilation: no
Materials: README NEWS
In views: TimeSeries
CRAN checks: StructuralDecompose results

Documentation:

Reference manual: StructuralDecompose.pdf
Vignettes: Decomposition
Example-Walkthrough
Introduction

Downloads:

Package source: StructuralDecompose_0.1.1.tar.gz
Windows binaries: r-devel: StructuralDecompose_0.1.1.zip, r-release: StructuralDecompose_0.1.1.zip, r-oldrel: StructuralDecompose_0.1.1.zip
macOS binaries: r-release (arm64): StructuralDecompose_0.1.1.tgz, r-oldrel (arm64): StructuralDecompose_0.1.1.tgz, r-release (x86_64): StructuralDecompose_0.1.1.tgz, r-oldrel (x86_64): StructuralDecompose_0.1.1.tgz

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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