This IMSTAT procedure
example demonstrates using higher-order polynomial models and also
model selection.
Both REGCORR statements
in the example request fitting a regression model of the response
variable, Sales, and the regressor variable, Inventory. If no variables
are specified, then the procedure fits a model for each pair of numeric
non-CLASS variables in the table.
Program
libname example sasiola host="grid001.example.com" port=10010 tag='hps';
data example.shoes; set sashelp.shoes; run;
proc imstat data=example.shoes;
regcorr sales inventory / order=2; 1
run;
regcorr sales inventory / order=-3; 2
run;
quit;
Program Description
This REGCORR statement uses the ORDER=2 option to
specify a quadratic model. ORDER=1 requests a linear model and ORDER=3
requests a cubic model.
Specifying -3 for the ORDER= option indicates that
the procedure perform model selection from linear, quadratic, and
cubic models. The procedure finds the best-fitting polynomial that
is most appropriate, according to statistical principles.
Output
The following display
shows the results for the two REGCORR statements. The first display
shows the results for the quadratic model that was requested with
ORDER=2. The second display shows the results for letting the procedure
determine the best fit of the model. In this case, because the Quadr
column has a nonzero value, that indicates the procedure determined
that the quadratic model fits the data best. If the Cubic column been
nonzero, that would indicate that the procedure selected the cubic
model as the most appropriate.