04-18-2017 09:26 AM
Stack overflow could not help me so and referred me here.
I want to find to find extreme values produced by a macro as a function of input parameters:
For example purposes here is some data:
data Input_data; input X Y; cards; 10 15 20 18 30 27 33 41 ; run;
The following is not the actual formula (as the minimum for this is easily found analytically.) and I want computational method. For examples sake I have semi-empirical rule, which takes three parameters in:
%macro Function(const1, const2 const3); data output; set input; X_eff1=((X > &const1.)*(X - &const1.)**2); X_eff2=((X > &const2.)*(X - &const2.)**2); X_eff3=((X > &const3.)*(X - &const3.)**2); Residual= Y - (1.3*X_eff1 - 2.7*X_eff2+ 3.1*X_eff3); run; %mend;
I want the find const1, const2 const3 which produce the minimum value for variable 'Residual'. For sake of argument, lets say minimum of sum(abs(residual)).
Can SAS do this? Few options that are to be considered:
a) Find global minimum
b) Find local minimum within boundary conditions, for example:
I could generate huge table and brute force feed it to the function. However, this is not feasible if the number of input parameter rise.
I could scratch program something?
I could do this in numpy (fmin from cipy.optimize comes to mind)or R if it proves hard for SAS.
Any thoughts on how to solve it?
04-18-2017 09:49 AM
You could program it yourself in this fashion:
min_residual = 999;
do const1 = 0 to 1 by 0.01;
do const2 = 10 to 17 by 0.01;
do const3 = 20 to 22 by 0.01;
* Calculations using no macro variables, only const1 const2 and const3;
if abs(residual) < min_residual then do;
min_residual = abs(residual);
min_const1 = const1;
min_const2 = const2;
min_const3 = const3;
You can adjust the fineness of the grid, depending on how many constants you have, how many observations you have, and how much time you have to wait for the program to complete. Also, you may want to add another variable to track whether the minimum residual is positive or negative.
04-19-2017 01:32 AM
04-18-2017 09:56 AM - edited 04-18-2017 09:57 AM
The standard ways to solve an optimization problem (constrained or unconstrained) in SAS are:
2. PROC OPTMODEL in SAS/OR software provides a simpler syntax and a wide variety of solvers.
Do you have a license for either SAS/IML and/or SAS/OR software?
04-19-2017 01:33 AM
These are the packages I hae access to:
PROC SETINIT; run;
-Base SAS Software
---SAS Enterprise Guide
---SAS/ACCESS Interface to PC Files
---SAS/ACCESS Interface to OLE DB
---SAS Workspace Server for Local Access
---High Performance Suite
04-18-2017 10:19 AM