SAS Code for Smoothplot

Data defines the model by dint of genetic programming, producing the best decile table.

SAS Code for Smoothplot
Bruce Ratner, PhD

~~~~~~~~~~~~~~~~~~~~~~~

%let X=X1;
%let slice_X=10;
title " Smoothplot - Y (0-1) vs. &X ";

data IN;
input X1 X2;
cards;
13 14
17 19
54 43
23 88
11 77
09 33
32 53
10 12
51 52
13 14
17 19
43 10
88 98
77 25
33 76
53 41
12 15
52 53
83 76
43 41
13 14
17 19
32 53
10 12
51 52
13 14
17 19
43 10
88 98
77 25
33 76
53 41
12 15
52 53
83 76
43 41
;
run;

data IN;
set IN;
Y=RAND('BERNOULLI', 1/3) ;

data smooth;
set IN;
wt=1;
run;
proc print;
run;

data score;
set smooth;
keep wt Y &X;
run;

data notdot;
set score;
if &X ne .;
proc means data=notdot sum noprint;var wt;
output out=samsize (keep=samsize) sum=samsize;
run;

data scoresam (drop=samsize);
set samsize score;
retain n;
if _n_=1 then n=samsize;
if _n_=1 then delete;
run;

proc sort data=scoresam;by descending &X ;
run;

data score_X;
set scoresam;
if &X ne . then cum_n+wt;
if &X = . then slice_X =.;
else slice_X=floor(cum_n*&slice_X/(n+1));
drop cum_n n;
run;

proc summary data=score_X nway;
class slice_X ;
var &X Y;
output out=smout_&X mean= sm_&X sm_&Y/noinherit;
run;

proc print data=smout_&X;
run;

data sliced_X;
set smout_&X;
logit_Y=log( sm_Y/(1-sm_Y));
if sm_Y=1 then logit_Y= 7;
if sm_Y=0 then logit_Y=-7;
Prob_Y= exp(logit_Y)/((1+exp(logit_Y)));
proc print data=sliced_X;
run;

proc plot data=sliced_X HPCT=80 VPCT=80;plot logit_Y*sm_&X;
format logit_Y 6.2;
run;

proc plot data=sliced_X HPCT=80 VPCT=80;plot Prob_Y*sm_&X;
format Prob_&Y 6.2;
run;
quit;

For more information about this article, call Bruce Ratner at 516.791.3544 or 1 800 DM STAT-1; or e-mail at br@dmstat1.com.

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