Fnextp.test: Test for the Significance of the p+1 Autoregressive...
In partsm: Periodic Autoregressive Time Series Models

Description Usage Arguments Value Author(s) References See Also Examples

Test for the significance of prospective autoregressive parameters of order p+1 in an AR(p) or PAR(p) model. It is performed as an F-statistic that sets the parameters of order p+1 equal to zero.

1 2	Fnextp.test (wts, detcomp, p, type)

`wts`	a univariate time series object.
`detcomp`	a vector indicating the deterministic components included in the auxiliary regression. See the corresponding item in `fit.ar.par`.
`p`	the order of the initial AR or PAR model.
`type`	a character string indicating whether the model to fit is an autoregressive model, `"AR"`, or a periodic autoregressive model, `"PAR"`.

An object of class Ftest.partsm-class containing the F-test statistic, the freedom degrees an the corresponding p-value.

Javier Lopez-de-Lacalle javlacalle@yahoo.es.

P.H. Franses: Periodicity and Stochastic Trends in Economic Time Series (Oxford University Press, 1996).

fit.ar.par, and Ftest.partsm-class.

    ## Test the significance of a second order lag in a PAR model for the Real GNP in Germany.
    ## Including seasonal intercepts.
    data("gergnp")
    lgergnp <- log(gergnp, base=exp(1))
    detcomp <- list(regular=c(0,0,0), seasonal=c(1,0), regvar=0)
    out <- Fnextp.test(wts=lgergnp, detcomp=detcomp, p=1, type="PAR")