Example 25.1 Series J from Box and Jenkins
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 25.1.1.
Output 25.1.1
Results for Automatically Selected Model
-0.05683 |
1.072766 |
53.50912 |
3.202121 |
The STATESPACE Procedure
651.3862 |
-1033.57 |
-1632.96 |
-1645.12 |
-1651.52 |
-1648.91 |
-1649.34 |
-1643.15 |
-1638.56 |
-1634.8 |
-1633.59 |
+- |
+- |
+- |
+- |
+- |
+- |
+- |
+- |
+- |
+- |
+- |
-+ |
-+ |
-+ |
-+ |
-+ |
-+ |
-+ |
-+ |
-+ |
-+ |
-+ |
Output 25.1.2
Results for Automatically Selected Model
+. |
-. |
+. |
.. |
.. |
-. |
.. |
.. |
.. |
.. |
-+ |
-- |
-. |
.+ |
.. |
.. |
.. |
.. |
.. |
.+ |
1.925887 |
-0.00124 |
-1.20166 |
0.004224 |
0.116918 |
-0.00867 |
0.104236 |
0.003268 |
0.050496 |
1.299793 |
-0.02046 |
-0.3277 |
-0.71182 |
-0.25701 |
0.195411 |
0.133417 |
Output 25.1.3
Results for Automatically Selected Model
The STATESPACE Procedure
Canonical Correlations Analysis
1 |
1 |
0.804883 |
292.9228 |
304.7481 |
8 |
Output 25.1.4
Results for Automatically Selected Model
The STATESPACE Procedure
Selected Statespace Form and Preliminary Estimates
x(T;T) |
y(T;T) |
x(T+1;T) |
y(T+1;T) |
y(T+2;T) |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
-0.84718 |
0.026794 |
1.711715 |
-0.05019 |
0 |
0 |
0 |
0 |
0 |
1 |
-0.19785 |
0.334274 |
-0.18174 |
-1.23557 |
1.787475 |
1 |
0 |
0 |
1 |
1.925887 |
-0.00124 |
0.050496 |
1.299793 |
0.142421 |
1.361696 |
Output 25.1.5
Results for Automatically Selected Model
0.035274 |
-0.00734 |
-0.00734 |
0.097569 |
Output 25.1.6
Results for Automatically Selected Model
The STATESPACE Procedure
Selected Statespace Form and Fitted Model
x(T;T) |
y(T;T) |
x(T+1;T) |
y(T+1;T) |
y(T+2;T) |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
-0.86192 |
0.030609 |
1.724235 |
-0.05483 |
0 |
0 |
0 |
0 |
0 |
1 |
-0.34839 |
0.292124 |
-0.09435 |
-1.09823 |
1.671418 |
1 |
0 |
0 |
1 |
1.92442 |
-0.00416 |
0.015621 |
1.258495 |
0.08058 |
1.353204 |
Output 25.1.7
Results for Automatically Selected Model
0.035579 |
-0.00728 |
-0.00728 |
0.095577 |
-0.86192 |
0.072961 |
-11.81 |
0.030609 |
0.026167 |
1.17 |
1.724235 |
0.061599 |
27.99 |
-0.05483 |
0.030169 |
-1.82 |
-0.34839 |
0.135253 |
-2.58 |
0.292124 |
0.046299 |
6.31 |
-0.09435 |
0.096527 |
-0.98 |
-1.09823 |
0.109525 |
-10.03 |
1.671418 |
0.083737 |
19.96 |
1.924420 |
0.058162 |
33.09 |
-0.00416 |
0.035255 |
-0.12 |
0.015621 |
0.095771 |
0.16 |
1.258495 |
0.055742 |
22.58 |
0.080580 |
0.151622 |
0.53 |
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 25.1.1 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 25.1.8.
Output 25.1.8
STATESPACE Output for Transfer Function Model
The STATESPACE Procedure
Selected Statespace Form and Fitted Model
x(T;T) |
y(T;T) |
x(T+1;T) |
y(T+1;T) |
y(T+2;T) |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
-0.68882 |
0 |
1.598717 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
-0.35944 |
0.284179 |
-0.0963 |
-1.07313 |
1.650047 |
1 |
0 |
0 |
1 |
1.923446 |
0 |
0 |
1.260856 |
0 |
1.346332 |
Output 25.1.9
STATESPACE Output for Transfer Function Model
0.036995 |
-0.0072 |
-0.0072 |
0.095712 |
-0.68882 |
0.050549 |
-13.63 |
1.598717 |
0.050924 |
31.39 |
-0.35944 |
0.229044 |
-1.57 |
0.284179 |
0.096944 |
2.93 |
-0.09630 |
0.140876 |
-0.68 |
-1.07313 |
0.250385 |
-4.29 |
1.650047 |
0.188533 |
8.75 |
1.923446 |
0.056328 |
34.15 |
1.260856 |
0.056464 |
22.33 |
1.346332 |
0.091086 |
14.78 |
Copyright
© 2008 by SAS Institute Inc., Cary, NC, USA. All
rights reserved.