meansq

One point in \(\rm I\!R^{(p+q)}\).

dim.ar

dim.ma

Computes the mean square of the time series at the point <code>x</code>, will be minimize with the <code><a rd-options="stats" href="/link/optim?package=weakARMA&version=1.0.3&to=stats" data-mini-rdoc="stats::optim">optim</a></code> function in our function <code><a rd-options="" href="/link/estimation?package=weakARMA&version=1.0.3" data-mini-rdoc="weakARMA::estimation">estimation</a></code>.

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 Zako<c3><af>an, J. (1998) <doi:10.1016/S0378-3758(97)00139-0> and
Boubacar Ma<c3><af>nassara, Y. and Saussereau, B. (2018)
<doi:10.1080/01621459.2017.1380030> for more details.

Julien Yves Rolland

weakARMA

Tools for the Analysis of Weak ARMA Models

Yacouba Boubacar Ma<c3><af>nassara

Coraline Parguey

Vincent Mouillot

meansq function

Computes the mean square of the time series at the point <code>x</code>, will be minimize with the <code><a rd-options='stats' href='optim'>optim</a></code> function in our function <code><a rd-options='' href='estimation'>estimation</a></code>.

meansq: Function optim will minimize

Description

Usage

Arguments

Value