Decomposes a Level Shifted Time Series
Overview
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.
- Changed CRAN version to 0.1.1
- Fixed spelling in Description file by enclosing package names in single quotes
From NEWS.md in the release
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-03-10
Documentation
- Help pages
- 8
- Examples that run
- 100%7 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 0%
- Decomposition HTML
- Example-Walkthrough HTML
- Introduction HTML
Downloads
Repository
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Dependencies
Installing StructuralDecompose adds 5 packages (3 with compiled code, 3.4 MB of source tarballs). Heaviest: sandwich 1.4 MB, strucchange 751 KB, zoo 675 KB.
Code & Tests
Datasets
People & History
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- 0.1.1Latest2023-02-13 · current release
- RR 4.2.0 released · 2022-04-22
Package metadata
- First published
- 2023-02-13
- Total releases
- 1 / 3 yrs
- License
- MIT + file LICENSE OSI
- Minimum R
- ≥ 2.10
- Bundled data
- 0.3 KB / 1 file
- Download size
- 85 KB
Cite
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Run in R for the authors' preferred citation:
citation("StructuralDecompose")This package has no citation file, so citation() returns this entry built from DESCRIPTION.
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From data release v2026-10-25, which the citation names so these numbers can be found later. More on citing and the projects behind them.