Fitting Curves and Surfaces Using SAS Software - ISS - University of ...

Fitting Curves and Surfaces Using SAS Software
Version 1.1 (February 2007)
(viii) Open the file loess3.sas. (The code is shown below).
proc loess data=Results;
by SmoothingParameter;
ods output OutputStatistics=residout;
model Residual=Year/smooth=0.3;
run;
(ix) Submit the program by pressing F8.
The results are stored in the output data set residout.
(x) Open the file loess3g.sas. (The program and the graphs produced are shown below).
(xi) Submit the program by pressing F8. The program plots the results in the same fashion as before using
PROC GREPLAY.
axis1 label = (angle=90 rotate=0)
order = (-0.8 to 0.8 by 0.4);
goptions nodisplay;
proc gplot data=residout;
by SmoothingParameter;
plot DepVar*Year
Pred*Year/&opts vref=0 lv=2
vm=1 name='resids';
run;
goptions display ;
proc greplay nofs tc=sashelp.templt
template=l2r2;
igout gseg;
treplay 1:resids 2:resids2
3:resids1 4:resids3;
run; quit;
title;
Residual plots for the four models
An inspection of these plots suggests that a value of 0.2 for the smoothing parameter provides a good
compromise between representing the general trend in the data and tracking the detailed fluctuations
about that trend.
If the observations are independently and identically distributed and follow the Normal distribution, we
can obtain confidence limits for the model predictions by adding the clm option in the model
statement. By default, 95% limits are produced, but this can be changed by using the alpha= option in
the model statement.
(xii) To complete this sequence, open the file loess4.sas.
(xiii) This final step specifies alpha=0.1, causing 90% confidence limits to be included in the Results
data set and produces the fitted curve with confidence limits superimposed. The program and the
graph are shown below.
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Version 1.1 (Feb 2007) tut125.doc