acf.gamma_m: Computation of autocovariance and autocorrelation for an ARMA...

In weakARMA: Tools for the Analysis of Weak ARMA Models

Computation of autocovariance and autocorrelation for an ARMA residuals.

Description

Computes empirical autocovariances and autocorrelations function for an ARMA process for lag max given.

Usage

acf.gamma_m(ar = NULL, ma = NULL, y, h, e = NULL)

Arguments

ar	Vector of AR coefficients. If NULL, it is a MA process.
ma	Vector of MA coefficients. If NULL, it is a AR process.
y	Univariate time series.
h	Computes autocovariances and autocorrelations from lag 1 to lag h with h an integer.
e	Vector of residuals. If NULL, the function will compute it.

Value

A list with :

gamma_m

Vector of the autocovariances.

rho_m

Vector of the autocorrelations.

See Also

acf.univ for autocorrelation and autocovariance for only one given lag h.

Examples

param.estim <- estimation(p = 1,  q = 1, y = CAC40return.sq)
acf.gamma_m(ar = param.estim$ar, ma = param.estim$ma, y = CAC40return.sq,  h = 20)

weakARMA documentation built on April 5, 2022, 1:16 a.m.