# Example for model identification and forecasting 
# Generate some training data.
set.seed(1)
series1 <- arima.sim(model=list(order=c(2,1,2), ar=c(.4, .2), ma=c(.3,.1)), n=500)

# Graph the data..
par(mfrow=c(3,2))
plot(series1)
title("ARIMA(2,1,2)")
plot(diff(series1))
title("Differenced")
acf(series1)
acf(diff(series1))
acf(series1, type="partial")
acf(diff(series1), type="partial")

# fit ARIMA model 
fit <- arima(series1, order=c(2,1,2))