# Rolling forecasts: training versus forecast accuracy evaluation

Questions:

1. Are rolling forecast examples (like the ones below) only useful for evaluating a model's accuracy, or can a rolling forecast be used to train a model?
2. Are models trained using a rolling forecast generally more accurate?
3. Can anyone point out an example of a model being trained using a rolling window/rolling forecast technique and forecasted horizons in to the future? By that I mean forecasted horizons beyond the training/testing data used in the rolling forecast.

Code:

library("fpp")

h <- 5
train <- window(hsales,end=1989.99)
test <- window(hsales,start=1990)
n <- length(test) - h + 1
fit <- auto.arima(train)
fc <- ts(numeric(n), start=1990+(h-1)/12, freq=12)
for(i in 1:n)
{
x <- window(hsales, end=1989.99 + (i-1)/12)
refit <- Arima(x, model=fit)