Package: weakARMA 1.0.3
Julien Yves Rolland
weakARMA: Tools for the Analysis of Weak ARMA Models
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.
Authors:
weakARMA_1.0.3.tar.gz
weakARMA_1.0.3.tar.gz(r-4.5-noble)weakARMA_1.0.3.tar.gz(r-4.4-noble)
weakARMA_1.0.3.tgz(r-4.4-emscripten)weakARMA_1.0.3.tgz(r-4.3-emscripten)
weakARMA.pdf |weakARMA.html✨
weakARMA/json (API)
| # Install 'weakARMA' in R: |
| install.packages('weakARMA', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- CAC40 - Paris stock exchange
- CAC40return - Paris stock exchange return
- CAC40return.sq - Paris stock exchange square return
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 years agofrom:174ecc3645. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Sep 04 2024 |
| R-4.5-linux | OK | Sep 04 2024 |
Exports:acf.gamma_macf.univARMA.selecestimationgradientmatXimeansqnl.acfomegaportmanteauTestsignifparamsim.ARMAsimGARCHVARestwnPTwnPT_SQwnRT
Dependencies:CompQuadFormlatticelmtestMASSmatrixStatsnlmesandwichstrucchangeurcavarszoo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Computation of autocovariance and autocorrelation for an ARMA residuals. | acf.gamma_m |
| Computation of autocovariance and autocorrelation for an ARMA residuals. | acf.univ |
| Selection of ARMA models | ARMA.selec |
| Paris stock exchange | CAC40 |
| Paris stock exchange return | CAC40return |
| Paris stock exchange square return | CAC40return.sq |
| Parameters estimation of a time series. | estimation |
| Computation the gradient of the residuals of an ARMA model | gradient |
| Estimation of Fisher information matrix I | matXi |
| Function optim will minimize | meansq |
| Autocorrelogram | nl.acf |
| Computation of Fisher information matrice | omega |
| Portmanteau tests | portmanteauTest |
| Portmanteau tests for one lag. | portmanteauTest.h |
| Computes the parameters significance | signifparam |
| Simulation of ARMA(p,q) model. | sim.ARMA |
| GARCH process | simGARCH |
| Estimation of VAR(p) model | VARest |
| Weak white noise | wnPT |
| Weak white noise | wnPT_SQ |
| Weak white noise | wnRT |