Package: StructuralDecompose 0.1.1

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.

Authors:Allen Sunny [aut, cre]

StructuralDecompose_0.1.1.tar.gz
StructuralDecompose_0.1.1.zip(r-4.7)StructuralDecompose_0.1.1.zip(r-4.6)StructuralDecompose_0.1.1.zip(r-4.5)
StructuralDecompose_0.1.1.tgz(r-4.6-any)StructuralDecompose_0.1.1.tgz(r-4.5-any)
StructuralDecompose_0.1.1.tar.gz(r-4.7-any)StructuralDecompose_0.1.1.tar.gz(r-4.6-any)
StructuralDecompose_0.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
StructuralDecompose/json (API)

# Install 'StructuralDecompose' in R:
install.packages('StructuralDecompose', repos = c('https://allen-1242.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/allen-1242/structuraldecompose/issues

Pkgdown/docs site:https://allen-1242.github.io

Datasets:

On CRAN:

Conda:

decompositiontimeseries-analysis

5.18 score 2 stars 10 scripts 242 downloads 7 exports 8 dependencies

Last updated from:d18a7a6cee. Checks:7 ERROR, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64ERROR164
source / vignettesOK268
linux-release-x86_64ERROR122
macos-release-arm64ERROR107
macos-oldrel-arm64ERROR130
windows-develERROR79
windows-releaseERROR67
windows-oldrelERROR85
wasm-releaseOK99

Exports:AnomalyDetectionBreakPointsLevelCheckMeanCleaningMedianCleaningSmoothingStructuralDecompose

Dependencies:changepointlatticeMASSnlmesandwichsegmentedstrucchangezoo

Example-Walkthrough
Introduction | Getting Started | Loading the Data | Decomposition
Rendered fromExample-Walkthrough.Rmdusingknitr::rmarkdown

Last update: 2026-06-13
Started: 2023-02-05

Introduction
Rendered frompackage_intro.Rmdusingknitr::rmarkdown

Last update: 2025-06-10
Started: 2023-01-08

Decomposition
Introduction | Trend | Seasonality
Rendered fromDecomposition.Rmdusingknitr::rmarkdown

Last update: 2023-02-05
Started: 2023-01-19