I have come across this strange case in SAS Time Series Forecasting System and it seems that SAS is displaying wrong estimates.
Here is a simple example.
When I fit a quadratic trend to my dataset using TSFS, I get the following estimates:
3.85465 |
0.3471 |
11.1041 |
<.0001 |
-0.03373 |
0.0089 |
-3.7788 |
0.0003 |
-0.00117 |
0.000353 |
-3.3153 |
0.0013 |
5.08917 |
. |
. |
. |
Now, when I run a simple regression (proc reg) on the same dataset, using proc reg, I get totally different results
1 |
2.52733 |
0.71316 |
3.54 |
0.0006 |
1 |
0.08578 |
0.03465 |
2.48 |
0.0152 |
1 |
-0.00117 |
0.00035340 |
-3.32 |
0.0013 |
Interestingly, the oredicted values shown by TSFS system seem to be following the estimates shown by the PROC REG.
Here is the predicted values of TSFS for the first three observations
NOV2009 |
1.0000 |
2.6119 |
7.0335 |
-1.8096 |
-1.6119 |
2.2559 |
-0.7145 |
-50 |
2500 |
DEC2009 |
2.0000 |
2.6942 |
7.1157 |
-1.7273 |
-0.6942 |
2.2559 |
-0.3077 |
-49 |
2401 |
JAN2010 |
4.0000 |
2.7741 |
7.1956 |
-1.6474 |
1.2259 |
2.2559 |
0.5434 |
-48 |
2304 |
The values in the fourth column (Predicted value for INCIDENTS) are based the parameter estimates form PROC REG and not the estimates from TSFS. for example, for first observations:
2.52733+ 0.08578*1 -0.00117*(1^2)=2.6119
I noticed that this discrepancy between the estimates of proc OLS and TSFS happens only when there are high order terms included in the model (such as quadratic or cubic).
Why is this happening and how can I get correct estimates using TSFS.