Database Reference
In-Depth Information
Exercises
1. Why use autocorrelation instead of autocovariance when examining
stationary time series?
2. Provide an example that if the cov(X, Y) = 0, the two random variables, X
and Y, are not necessarily independent.
3. Fit an appropriate ARIMA model on the following datasets included in R.
Provide supporting evidence on why the fitted model was selected, and
forecast the time series for 12 time periods ahead.
a.
faithful:
Waiting times (in minutes) between Old Faithful geyser
eruptions
b.
JohnsonJohnson:
Quarterly earnings per J&J share
c.
sunspot.month:
Monthly sunspot activity from 1749 to 1997
4. When should an ARIMA(p,d,q) model in which d > 0 be considered instead
of an ARMA(p,q) model?
