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);
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;
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
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;
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;
Many thanks.
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