# robustChangeExamples.ssc

plot(frip.dat)
frip.rr = arima.rob(log(frip.dat)~1, p=2, d=1)

frip.t = 1:length(frip.dat)
tmp = arima.rob(log(frip.dat)~frip.t-1, p=2, d=1)

summary(frip.rr)

plot(frip.rr)

import.rr = arima.rob(import~taxes-1, data=import.dat, p=2, d=1)
import.hat = predict(import.rr, 10, newdata=newtaxes.dat, se=T)
class(import.hat)
names(import.hat)
plot(import.hat, import.dat[, "import"])

frip.srr = arima.rob(log(frip.dat)~1, p=2, d=1, sfreq=12, sma=T)
summary(frip.srr)

frip.nrr = arima.rob(log(frip.dat)~1, p=2, d=1, sma=T, 
                     sfreq=12, innov.outlier=T)

summary(outliers(frip.nrr))

frip.irr = arima.rob(log(frip.dat)~1, p=2, d=1, iter=T)
summary(frip.irr)

summary(outliers(frip.irr, iter=2))