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-any)StructuralDecompose_0.1.1.zip(r-4.6-any)StructuralDecompose_0.1.1.zip(r-4.5-any)
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

4.95 score 2 stars 5 scripts 322 downloads 7 exports 8 dependencies

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

TargetResultTimeFilesSyslog
linux-develERROR113
source / vignettesOK197
linux-releaseERROR120
macos-releaseERROR153
macos-oldrelERROR152
windows-develERROR74
windows-releaseERROR61
windows-oldrelERROR72
wasm-releaseOK103

Exports:AnomalyDetectionBreakPointsLevelCheckMeanCleaningMedianCleaningSmoothingStructuralDecompose

Dependencies:changepointlatticeMASSnlmesandwichsegmentedstrucchangezoo

Example-Walkthrough
Introduction | Getting Started | Loading the Data | Decomposition

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

Introduction

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

Decomposition
Introduction | Trend | Seasonality

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