Winsorized output file

[Almutairi]

Hi all,

I am using this code written by Rick Wicklin and I got the results of means of all variables. But, I still do not see any output file that contains the winsorized data. Can any one help plz.

%let DSName = sashelp.heart;
proc iml;
/* SAS/IML module to Winsorize each column of a matrix. 
   Input proportion of observations to Winsorize: prop < 0.5. 
   Ex:  y = Winsorize(x, 0.1) computes the two-side 10% Winsorized data */
start Winsorize(x, prop);
   p = ncol(x);            /* number of columns */
   w = x;                  /* copy of x */
   do i = 1 to p;
      z = x[,i];           /* copy i_th column */
      n = countn(z);       /* count nonmissing values */
      k = ceil(prop*n);    /* number of obs to trim from each tail */
      r = rank(z);         /* rank values in i_th column */
      /* find target values and obs with smaller/larger values */
      lowIdx = loc(r<=k & r^=.);
      lowVal = z[loc(r=k+1)]; 
      highIdx = loc(r>=n-k+1);
      highVal = z[loc(r=n-k)]; 
      /* Winsorize (replace) k smallest and k largest values */
      w[lowIdx,i] = lowVal;
      w[highIdx,i] = highVal;
   end;
   return(w);
finish;
 
/* test the algorithm on numerical vars in a data set */
use &DSName;
read all var _NUM_ into X[colname=varNames];
close;
winX = Winsorize(X, 0.1);

[Reeza]

I don't believe that code actually writes back to the data set. It defines a function to winsorize and shows how it can be used. You would need to add the code to save it back to a data set.

However, this question was asked at least once if not twice this week, so a quick search within the time frame should get you some generic examples.

https://communities.sas.com/t5/SAS-Programming/winsoring-outliers/m-p/529770#M144807

[Ksharp · Accepted solution]

Check WANT table. P.S. since is a IML question, why not post it at IML forum , Rick is there ? 

%let DSName = sashelp.heart;
proc iml;
/* SAS/IML module to Winsorize each column of a matrix. 
   Input proportion of observations to Winsorize: prop < 0.5. 
   Ex:  y = Winsorize(x, 0.1) computes the two-side 10% Winsorized data */
start Winsorize(x, prop);
   p = ncol(x);            /* number of columns */
   w = x;                  /* copy of x */
   do i = 1 to p;
      z = x[,i];           /* copy i_th column */
      n = countn(z);       /* count nonmissing values */
      k = ceil(prop*n);    /* number of obs to trim from each tail */
      r = rank(z);         /* rank values in i_th column */
      /* find target values and obs with smaller/larger values */
      lowIdx = loc(r<=k & r^=.);
      lowVal = z[loc(r=k+1)]; 
      highIdx = loc(r>=n-k+1);
      highVal = z[loc(r=n-k)]; 
      /* Winsorize (replace) k smallest and k largest values */
      w[lowIdx,i] = lowVal;
      w[highIdx,i] = highVal;
   end;
   return(w);
finish;
 
/* test the algorithm on numerical vars in a data set */
use &DSName;
read all var _NUM_ into X[colname=varNames];
close;
winX = Winsorize(X, 0.1);

create want from winX[c=varNames];
append from winX;
close;
quit;

[Ksharp]

And here is my code.

data have;
 do i=1 to 100;
  a=ceil(ranuni(1)*100);
  b=ceil(ranuni(2)*100);
  output;
 end;
 drop i;
run;


%let low=0.05 ;
%let high=0.95 ;

proc iml;
use have;
read all var _num_ into x[c=vname];
close have;
call qntl(q,x,{&low ,&high});

do i=1 to ncol(x);
 x[loc(x[,i]<q[1,i]),i]=q[1,i];
 x[loc(x[,i]>q[2,i]),i]=q[2,i];
end;

create want from x[c=vname];
append from x;
close want;

quit;

[Almutairi]

Many thanks.