First Getting Started Example for PROC FMM
/****************************************************************/
/* S A S S A M P L E L I B R A R Y */
/* */
/* NAME: fmmgs1 */
/* TITLE: First Getting Started Example for PROC FMM */
/* Mixtures of binomial distributions */
/* PRODUCT: STAT */
/* SYSTEM: ALL */
/* KEYS: Student's yeast cell counts */
/* Maximum likelihood and Bayesian analysis */
/* PROCS: FMM */
/* DATA: */
/* */
/* SUPPORT: Dave Kessler */
/* REF: Pearson, K. (1915), On certain types of compound */
/* frequency distributions in which the components */
/* can be individually described by binomial series. */
/* Biometrika, 11, 139--144. */
/* MISC: */
/****************************************************************/
data yeast;
input count f;
n = 5;
datalines;
0 213
1 128
2 37
3 18
4 3
5 1
;
proc fmm data=yeast;
model count/n = / k=2;
freq f;
run;
proc fmm data=yeast;
model count/n = / k=2;
freq f;
output out=fmmout pred(components) posterior;
run;
data fmmout;
set fmmout;
PredCount_1 = post_1 * f;
PredCount_2 = post_2 * f;
run;
proc print data=fmmout;
run;
ods graphics on;
proc fmm data=yeast seed=12345;
model count/n = / k=2;
freq f;
performance cpucount=2;
bayes;
run;
ods graphics off;