- Table B.6 supplied to you contains global mean surface air temperature anomaly. Develop an appropriate ARIMA model and a method for forecasting
- Table B7. contains Whole Foods Market Stock Price daily closings Use the first 85% of the data and build an appropriate A RIMA model Come up with a forecasting method . Check your one-day two-day and three-day forecasts on the other 15% is of the dataset
- inc.dat contains gas pressure data from a utility company. Construct an appropriate ARIMA model. Report 95% prediction intervals and forecasts for a few time units
- Consider the ARIMA (0,1,1) model: (1 – B)Yt = (1 – ƟB)Ɛt
Show that the one-step forecast is:
Ŷt+1 = Yt– ƟƐt
Ŷt+h= Ŷt+h-1 , h ≥ 2
- Let {Yt} be a covariance stationary process with h-log correlation ƍhand variance σ2. Derive an expression for the variance of the sample mean
= n-1 i