partsm (version 1.1-4)

Fnextp.test: Test for the Significance of the p+1 Autoregressive Parameters in an AR(p) or PAR(p) Model

Description

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.

Usage

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

Value

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

Arguments

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".

Author

Javier Lopez-de-Lacalle .

References

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

See Also

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

Examples

    ## 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")