portmanteauTest {weakARMA}

Portmanteau tests

Description

Realizes portmanteau tests of the first m lags, this function uses portmanteauTest.h for h in 1:m.

Usage

portmanteauTest(ar = NULL, ma = NULL, y, m = NULL)

Arguments

ar

Vector of AR coefficients. If NULL, it is a MA process.

ma

Vector of MA coefficients. If NULL, it is an AR process.

y

Univariate time series.

m

Integer for the lag.

Value

A list of vectors of length m, corresponding to statistics and p-value for each lag, for standard, modified and self-normalized Ljung-Box and Box-Pierce methods.

References

Boubacar Maïnassara, Y. 2011, Multivariate portmanteau test for structural VARMA models with uncorrelated but non-independent error terms Journal of Statistical Planning and Inference, vol. 141, no. 8, pp. 2961-2975.

Boubacar Maïnassara, Y. and Saussereau, B. 2018, Diagnostic checking in multivariate ARMA models with dependent errors using normalized residual autocorrelations , Journal of the American Statistical Association, vol. 113, no. 524, pp. 1813-1827.

Francq, C., Roy, R. and Zakoïan, J.M. 2005, Diagnostic Checking in ARMA Models with Uncorrelated Errors, Journal of the American Statistical Association, vol. 100, no. 470, pp. 532-544.

See Also

portmanteauTest.h to obtain statistics for only one h lag.

Examples

 est<-estimation(p = 1, q = 1, y = CAC40return.sq)
 portmanteauTest(ar = est$ar, ma = est$ma, y = CAC40return.sq, m = 20)