acf.univ: 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 functions for an ARMA process for only one given lag.

Usage

acf.univ(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	Given lag to compute autocovariance and autocorrelation, with h an integer.
e	Vector of residuals of the time series. If NULL, the function will compute it.

Value

A list with :

autocov

Value of the autocovariance.

autocor

Value of the autocorrelation.

See Also

acf.gamma_m for autocorrelation and autocovariance for all h lag.

Examples

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

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