Autocorrelation Check for White Noise To Chi- DF Pr > Autocorrelations Lag Square ChiSq 81.84 6 0.867 0.663 0.439 0.214 6 <.0001 0.005 0.184 12 142.96 12 <.0001 Data autocorrelated predictable! Note: All p-values are on an assumption called discussed later. “stationarity” How to predict? One step prediction Two step prediction variance ( = variance(et) ) 2 Prediction error
Autocorrelation Check for White Noise To Lag DF Pr > ChiSq Autocorrelations 6 81.84 6 <.0001 0.867 0.663 0.439 0.214 12 142.96 12 <.0001 Data autocorrelated predictable! Note: All p-values are on an assumption called “stationarity” discussed later. How to predict? One step prediction Two step prediction Prediction error variance ( 2 = variance(et) ) Chi- Square 0.005 0.184