plotpredpiar: Plot of the Out-of-Sample Forecasts in a PIAR Model
In partsm: Periodic Autoregressive Time Series Models

Description Usage Arguments Author(s) References See Also Examples

This function displays a plot of the predictions and the corresponding 95 per cent confidence intervals based on a PIAR model. In this version, this function is implemented for quarterly observed data, PIAR models up to order 2 are considered, and seasonal intercepts are included by default.

1 2	plotpredpiar (x)

`x`	Object of class 'pred.piartsm'.

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

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

pred.piartsm-class, and predictpiar.

    ## Load data and select the deterministic components.
    data("gergnp")
    lgergnp <- log(gergnp, base=exp(1))

    ## Fit a PIAR(2) model with seasonal intercepts.
    out.pred <- predictpiar(wts=lgergnp, p=2, hpred=24)
    plotpredpiar(out.pred)