This example analyzes the gas furnace data (series J) from Box and Jenkins. (The data are not shown; see Box and Jenkins (1976) for the data.)
First, a model is selected and fit automatically using the following statements.
title1 'Gas Furnace Data'; title2 'Box & Jenkins Series J'; title3 'Automatically Selected Model'; proc statespace data=seriesj cancorr; var x y; run;
The results for the automatically selected model are shown in Output 35.1.1.
Output 35.1.1: Results for Automatically Selected Model
Gas Furnace Data |
Box & Jenkins Series J |
Automatically Selected Model |
Information Criterion for Autoregressive Models | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|
Lag=0 | Lag=1 | Lag=2 | Lag=3 | Lag=4 | Lag=5 | Lag=6 | Lag=7 | Lag=8 | Lag=9 | Lag=10 |
651.3862 | -1033.57 | -1632.96 | -1645.12 | -1651.52 | -1648.91 | -1649.34 | -1643.15 | -1638.56 | -1634.8 | -1633.59 |
Output 35.1.2: Results for Automatically Selected Model
Output 35.1.3: Results for Automatically Selected Model
Output 35.1.4: Results for Automatically Selected Model
Output 35.1.5: Results for Automatically Selected Model
Output 35.1.6: Results for Automatically Selected Model
Output 35.1.7: Results for Automatically Selected Model
Parameter Estimates | |||
---|---|---|---|
Parameter | Estimate | Standard Error |
t Value |
F(3,1) | -0.86192 | 0.072961 | -11.81 |
F(3,2) | 0.030609 | 0.026167 | 1.17 |
F(3,3) | 1.724235 | 0.061599 | 27.99 |
F(3,4) | -0.05483 | 0.030169 | -1.82 |
F(5,1) | -0.34839 | 0.135253 | -2.58 |
F(5,2) | 0.292124 | 0.046299 | 6.31 |
F(5,3) | -0.09435 | 0.096527 | -0.98 |
F(5,4) | -1.09823 | 0.109525 | -10.03 |
F(5,5) | 1.671418 | 0.083737 | 19.96 |
G(3,1) | 1.924420 | 0.058162 | 33.09 |
G(3,2) | -0.00416 | 0.035255 | -0.12 |
G(4,1) | 0.015621 | 0.095771 | 0.16 |
G(4,2) | 1.258495 | 0.055742 | 22.58 |
G(5,1) | 0.080580 | 0.151622 | 0.53 |
G(5,2) | 1.353204 | 0.091388 | 14.81 |
The two series are believed to have a transfer function relation with the gas rate (variable X) as the input and the CO concentration (variable Y) as the output. Since the parameter estimates shown in Output 35.1.1 support this kind of model, the model is reestimated with the feedback parameters restricted to 0. The following statements fit the transfer function (no feedback) model.
title3 'Transfer Function Model'; proc statespace data=seriesj printout=none; var x y; restrict f(3,2)=0 f(3,4)=0 g(3,2)=0 g(4,1)=0 g(5,1)=0; run;
The last two pages of the output are shown in Output 35.1.8.
Output 35.1.8: STATESPACE Output for Transfer Function Model
Output 35.1.9: STATESPACE Output for Transfer Function Model
Parameter Estimates | |||
---|---|---|---|
Parameter | Estimate | Standard Error |
t Value |
F(3,1) | -0.68882 | 0.050549 | -13.63 |
F(3,3) | 1.598717 | 0.050924 | 31.39 |
F(5,1) | -0.35944 | 0.229044 | -1.57 |
F(5,2) | 0.284179 | 0.096944 | 2.93 |
F(5,3) | -0.09630 | 0.140876 | -0.68 |
F(5,4) | -1.07313 | 0.250385 | -4.29 |
F(5,5) | 1.650047 | 0.188533 | 8.75 |
G(3,1) | 1.923446 | 0.056328 | 34.15 |
G(4,2) | 1.260856 | 0.056464 | 22.33 |
G(5,2) | 1.346332 | 0.091086 | 14.78 |