After studying the output from Example 37.1 and identifying the ARIMA part of the model as, for example, (0 1 1)(0 1 1) 12, you can replace the IDENTIFY statement with the ARIMA and ESTIMATE statements as follows:
proc x12 data=sales date=date; var sales; transform power=0; arima model=( (0,1,1)(0,1,1) ); estimate; run ;
The parameter estimates and estimation summary statistics are shown in Output 37.2.1.
Output 37.2.1: Estimation Data
Estimation Summary | |
---|---|
For Variable sales | |
Number of Observations | 144 |
Number of Residuals | 131 |
Number of Parameters Estimated | 3 |
Variance Estimate | 1.3E-03 |
Standard Error Estimate | 3.7E-02 |
Standard Error of Variance | 1.7E-04 |
Log likelihood | 244.6965 |
Transformation Adjustment | -735.2943 |
Adjusted Log likelihood | -490.5978 |
AIC | 987.1956 |
AICC (F-corrected-AIC) | 987.3845 |
Hannan Quinn | 990.7005 |
BIC | 995.8211 |