partsm (version 1.1-4)

show-methods: Methods for Function 'show' in Package 'partsm'

Description

This method shows the information provided by functions implemented in package 'partsm'.

Methods

object = "fit.partsm".

Shows the estimates of the autoregressive or periodic autoregressive coefficients.

object = "Ftest.partsm".

Shows the \(F\)-test statistic, the null and the alternative hypotheses entailed in the procedure, as well as the freedom degrees, the \(p\)-value and a symbol indicating the significance of the \(F\)-statistic according to usual codes, i.e. Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1.

object = "fit.piartsm".

Shows the estimated periodic autoregressive coefficients in the restricted non-linear PIAR.

object = "LRur.partsm".

Shows the LR statistics and a one-side test constructed as \(sign(g(\hat{\alpha}) - 1) * LR^{1/2}\), where \(g(\hat{\alpha})\) is the product of the periodic differencing filter parameters estimated under the alternative.

object = "pred.piartsm".

Shows out-of-sample forecasts and the corresponding standard errors, as well as the 95 per cent confidence intervals.

Author

Javier Lopez-de-Lacalle .

See Also

fit.partsm-class, Ftest.partsm-class, and summary.

Examples

    ## Load data and select the deterministic components.
    data("gergnp")
    lgergnp <- log(gergnp, base=exp(1))
    detcomp <- list(regular=c(0,0,0), seasonal=c(1,0), regvar=0)

    ## Fit an AR(4) model with intercept and seasonal dummies.
    dcar <- list(regular=c(1,0,c(1,2,3)), seasonal=c(0,0), regvar=0)
    out.ar <- fit.ar.par(wts=lgergnp, type="AR", detcomp=dcar, p=4)
    show(out.ar)

    ## Fit a PAR(2) model with seasonal intercepts.
    out.par <- fit.ar.par(wts=lgergnp, type="PAR", detcomp=detcomp, p=2)
    show(out.par)

    ## Fnextp.test
    Fnextp.out <- Fnextp.test(wts=lgergnp, detcomp=detcomp, p=1, type="PAR")
    show(Fnextp.out)

    ## Fpar.test
    Fpar.out <- Fpar.test(wts=lgergnp, detcomp=detcomp, p=2)
    show(Fpar.out)

    ## Fsh.test
    ar4 <- fit.ar.par(wts=lgergnp, type="AR", p=4, detcomp=detcomp)
    Fsh.out <- Fsh.test(res=residuals([e-mail]), s=frequency(lgergnp))
    show(Fsh.out)

    ## Fit a PIAR(2) model with seasonal intercepts.
    out.piar <- fit.piar(wts=lgergnp, detcomp=detcomp, p=2)
    show(out.piar)

    ## Fpari.piar.test
    Fpari1.out <- Fpari.piar.test(wts=lgergnp, detcomp=detcomp, p=2, type="PARI1")
    show(Fpari1.out)

    ## Fit a PIAR(2) model with seasonal intercepts.
    out.piar <- fit.piar(wts=lgergnp, detcomp=detcomp, p=2)
    show(out.piar)

    ## Test for a single unit root in a PAR(2) model with seasonal intercepts.
    out.LR <- LRurpar.test(wts=lgergnp, detcomp=detcomp, p=2)
    show(out.LR)

    ## 24 step-ahead forecasts in a PIAR(2) model.
    pred.out <- predictpiar(wts=lgergnp, p=2, hpred=24)
    show(pred.out)