Documentation Example 2 for PROC DISTANCE
/****************************************************************/
/* S A S S A M P L E L I B R A R Y */
/* */
/* NAME: distanx2 */
/* TITLE: Documentation Example 2 for PROC DISTANCE */
/* PRODUCT: STAT */
/* SYSTEM: ALL */
/* KEYS: Distance Matrix, Cluster Analysis */
/* PROCS: DISTANCE, CLUSTER, PRINT */
/* DATA: */
/* */
/* SUPPORT: saswfk UPDATE: July 25, 2010 */
/* REF: PROC DISTANCE, Example 2 */
/* MISC: */
/* */
/****************************************************************/
title 'Stock Dividends';
data stock;
length Company $ 27;
input Company &$ Div_1986 Div_1987 Div_1988 Div_1989 Div_1990;
datalines;
Cincinnati G&E 8.4 8.2 8.4 8.1 8.0
Texas Utilities 7.9 8.9 10.4 8.9 8.3
Detroit Edison 9.7 10.7 11.4 7.8 6.5
Orange & Rockland Utilities 6.5 7.2 7.3 7.7 7.9
Kentucky Utilities 6.5 6.9 7.0 7.2 7.5
Kansas Power & Light 5.9 6.4 6.9 7.4 8.0
Union Electric 7.1 7.5 8.4 7.8 7.7
Dominion Resources 6.7 6.9 7.0 7.0 7.4
Allegheny Power 6.7 7.3 7.8 7.9 8.3
Minnesota Power & Light 5.6 6.1 7.2 7.0 7.5
Iowa-Ill Gas & Electric 7.1 7.5 8.5 7.8 8.0
Pennsylvania Power & Light 7.2 7.6 7.7 7.4 7.1
Oklahoma Gas & Electric 6.1 6.7 7.4 6.7 6.8
Wisconsin Energy 5.1 5.7 6.0 5.7 5.9
Green Mountain Power 7.1 7.4 7.8 7.8 8.3
;
proc distance data=stock method=dcorr out=distdcorr;
var interval(div_1986 div_1987 div_1988 div_1989 div_1990);
id company;
run;
proc print data=distdcorr;
id company;
title2 'Distance Matrix for 15 Utility Stocks';
run;
title2;
ods graphics on;
/* compute pseudo statistic versus number of clusters and create plot */
proc cluster data=distdcorr method=ward pseudo plots(only)=(psf dendrogram);
id company;
run;
/* compute pseudo statistic versus number of clusters and create plot */
proc cluster data=distdcorr method=average pseudo plots(only)=(psf dendrogram);
id company;
run;