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weakARMA  

Tools for the Analysis of Weak ARMA Models
View on CRAN: Click here


Download and install weakARMA package within the R console
Install from CRAN:
install.packages("weakARMA")

Install from Github:
library("remotes")
install_github("cran/weakARMA")

Install by package version:
library("remotes")
install_version("weakARMA", "1.0.3")



Attach the package and use:
library("weakARMA")
Maintained by
Julien Yves Rolland
[Scholar Profile | Author Map]
First Published: 2022-02-07
Latest Update: 2022-04-04
Description:
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.
How to cite:
Julien Yves Rolland (2022). weakARMA: Tools for the Analysis of Weak ARMA Models. R package version 1.0.3, https://cran.r-project.org/web/packages/weakARMA. Accessed 30 Apr. 2025.
Previous versions and publish date:
1.0.2 (2022-02-07 13:00)
Other packages that cited weakARMA R package
View weakARMA citation profile
Other R packages that weakARMA depends, imports, suggests or enhances
Complete documentation for weakARMA
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