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
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StructuralDecompose.pdf |StructuralDecompose.html
StructuralDecompose/json (API)
NEWS

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

Peer review:

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

Datasets:

On CRAN:

decompositiontimeseries-analysis

7 exports 1 stars 0.74 score 8 dependencies 4 scripts 242 downloads

Last updated 2 years agofrom:e442fd2d5f. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 18 2024
R-4.5-winOKSep 18 2024
R-4.5-linuxOKSep 18 2024
R-4.4-winOKSep 18 2024
R-4.4-macOKSep 18 2024
R-4.3-winOKSep 18 2024
R-4.3-macOKSep 18 2024

Exports:AnomalyDetectionBreakPointsLevelCheckMeanCleaningMedianCleaningSmoothingStructuralDecompose

Dependencies:changepointlatticeMASSnlmesandwichsegmentedstrucchangezoo

Decomposition

Rendered fromDecomposition.Rmdusingknitr::rmarkdownon Sep 18 2024.

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

Example-Walkthrough

Rendered fromExample-Walkthrough.Rmdusingknitr::rmarkdownon Sep 18 2024.

Last update: 2023-02-10
Started: 2023-02-05

Introduction

Rendered frompackage_intro.Rmdusingknitr::rmarkdownon Sep 18 2024.

Last update: 2023-01-19
Started: 2023-01-08