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weakARMA

1.0.3

Tools for the Analysis of Weak ARMA Models

0packages depend
2.7Kdownloads / year
test coverage
13/13checks pass

Overview

About
Maintained by Julien Yves RollandFirst published 2022-02-072 releasesCRAN page ↗

Numerous time series admit autoregressive moving average (ARMA) representations, in which the errors are uncorrelated but not necessarily independent. These models are called weak ARMA by opposition to the standard ARMA models, also called strong ARMA models, in which the error terms are supposed to be independent and identically distributed (iid). This package allows the study of nonlinear time series models through weak ARMA representations. It determines identification, estimation and validation for ARMA models and for AR and MA models in particular. Functions can also be used in the strong case. This package also works on white noises by omitting arguments 'p', 'q', 'ar' and 'ma'. See Francq, C. and Zakoïan, J. (1998) doi:10.1016/S0378-3758(97)00139-0 and Boubacar Maïnassara, Y. and Saussereau, B. (2018) doi:10.1080/01621459.2017.1380030 for more details.

Install

Health

CRAN checks
13OK
Slowest check: 2.0 min · r-oldrel-windows-x86_64
Code health
None
Tests · ratio 0.00
not tracked
Coverage
100%
Documentation · exports
4
Dependencies · direct
Check history
  • OK2026-08-04
    13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • NOTE2026-08-01
    12 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • OK2026-03-10
    14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

Documentation
READMEYes · 105 wordsVignettesNopkgdown siteNoNEWSNoCode of conductNoContributing guideNo
Examples that run
93%
Documented parameters
100%
Return-value docs
100%
References docs
52%

Downloads

2.7K
CRAN downloads in the past year
Rank #17,003 · ~7/day · ~228/mo
Daily download trend is not available in this view yet.
16230 days
62890 days
2.7K1 year
Compare downloads with other packages →
Also on98 r2u20 autocran

Dependencies

Declared dependencies
8 external dependencies (excludes base and recommended)
Depends (1)
R >= 3.4.1
LinkingTo (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Code & Tests

Datasets

People & History

People (4)
Maintainer (1)
Author, Maintainer
Authors (2)
Contributors (2)
Contributor
Contributor
Package Timeline

2 releases. Pick two to compare their code metrics. R releases are shown for context.

  • R
    R 4.6.0 released · 2026-04-24
  • R
    R 4.5.0 released · 2025-04-11
  • R
    R 4.4.0 released · 2024-04-24
  • R
    R 4.3.0 released · 2023-04-21
  • R
    R 4.2.0 released · 2022-04-22
  • 1.0.3Latest
    2022-04-04 · current release · diff ↗
  • 1.0.2
    2022-02-07
  • R
    R 4.1.0 released · 2021-05-18

Package metadata

First published
2022-02-07
Total releases
2 / 4 yrs
License
GPL (>= 3) OSI
Minimum R
≥ 3.4.1
Bundled data
144 KB / 3 files
Download size
171 KB
Installed size
not tracked yet
With dependencies
not tracked yet

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("weakARMA")
Rolland, J. Y., Boubacar Maïnassara, Y., Mouillot, V., & Parguey, C. (2022). weakARMA: Tools for the Analysis of Weak ARMA Models (Version 1.0.3) [Computer software]. https://doi.org/10.32614/CRAN.package.weakARMA

This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for weakARMA version 1.0.3 [Data set]. HJJB, LLC. Data release v2026-08-18. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-18, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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