Please open a new question instead of appending to a question that has been closed for 3 years.
Hi. Rick.
I think SQL can get what you want. But Due to your large number of variables, you need another macro to walk through all these variables.
NOTE: This way create about 3000 datasets to hold the similarity ,so it is less efficient than IML.
data a; input investor $ companyID $ wt; cards; A IBM 0.50 A MSFT 0.40 A GOOG 0.10 A GRPN 0.00 B IBM 0.40 B MSFT 0.60 B GOOG 0.00 B GRPN 0.00 C IBM 0.50 C MSFT 0.00 C GOOG 0.00 C GRPN 0.50 ; run; proc sort data=a; by companyID;run; proc transpose data=a out=temp(drop=_name_); by companyid; id investor; var wt; run; options nomprint nomlogic nosymbolgen; %macro across; proc sql ; select distinct investor from a; select distinct investor into :investor1 - :investor&sqlobs. from a; %let obs=&sqlobs ; %do i=1 %to %eval(&obs. - 1); create table _&i as select %do j=%eval(&i+1) %to &obs.; sum(&&investor&i*&&investor&j)/(sqrt(uss(&&investor&i))*sqrt(uss(&&investor&j))) as &&investor&i..&&investor&j %if &j ne &obs. %then %do;,%end; %end; from temp; %end; quit; %do k=1 %to %eval(&obs. - 1); data __&k; length name $ 40; set _&k; array _x{*} _numeric_; do i=1 to dim(_x); name=vname(_x{i});value=_x{i};output; end; keep name value; run; %end; data want; set __:; run; %mend across; %across
Ksharp
ksharp - just wanted to say thanks once more for all your help on this project. Results came out nicely ...
Rick
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