This method shows the information provided by functions implemented in package 'partsm'.
methods
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(α^)−1)∗LR1/2, where g(α^) 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.
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(ar4@lm.ar), 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)