Fnextp.test: Test for the Significance of the p+1 Autoregressive...

In partsm: Periodic Autoregressive Time Series Models

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)
  

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".

Value

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

Author(s)

Javier Lopez-de-Lacalle [e-mail].

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")
  

partsm documentation built on June 8, 2025, 10:33 a.m.