05-02-2015 12:58 AM
I know that there is couples of procedures can fit spline regression models such as PROC TRANSREG, PROC GLIMMIX, PROC TPSPLINE and so on.
What is the different between them? Could you please list other procedures?
Also, is there some procedures that can be used to reduce the number of variables in spline model? For example, I use Proc Transreg. The model statement is MODEL IDENTITY(Y) = SPLINE(X1 X2 X3 X4 ... X10), I try to remove all insignificant variables by some selection methods.
I did not find that the options such as Backward, Stepwise can be used for Transreg. Is there any other procedures I can use for this purpose?
05-02-2015 11:41 AM
Here is a good place to get started for more information:
And now with the EFFECT statement, you can get splines with several other procedures. But watch out, these splines would not necessarily be penalized smoothing. That is, if you put a spline effect in the model statement in GLIMMIX, it would fit a spline, but there would be no shrinkage of the parameters towards zero. You can get splines in GLIMMIX with random statements that are penalized/smoothing. Check out the radial smoothing example in the User's Guide.
As far as variable selection involving splines, I suggest the GLMSELECT procedure. If you have four variables, x1, x2, x3, x4, with splines for the first two (as an example):
model y = splx1 splx2 x3 x4 / selection = ___________;
There are many, MANY, options here, both for EFFECT and for selection.