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Generate all permutations in SAS

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By Topics | Advanced Analytics

In a previous post, I discussed how to generate random permutations of N elements. But what if you want to systematically iterate through a list of ALL permutations of N elements?

In the SAS DATA step you can use the ALLPERM subroutine in the SAS DATA step. For example, the following DATA step generates all permutations of five elements: 

%let n = 5;
/** generate all permutations of n elements, in order **/
data perm&n (drop=i);
array a{&n};
do i = 1 to &n; a[i]=i; end; /** initialize **/
do i = 1 to fact(&n);
   call allperm(i, of a[*]);
   output;
end;
run;

This creates a SAS data set named PERM5, which has 5! = 120 rows.

Beginning with SAS 9.3, you can also use the ALLPERM function in SAS/IML software, as follows: 

proc iml;
p5 = allperm(5);
print (p5[1:10,])[label="Permutations"];

The complete set of 120 permutations is stored in the p5 matrix, but only the first few rows are displayed.

Tags SAS Programming Statistical Programming Tips and Techniques
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About Author

Rick Wicklin

Distinguished Researcher in Computational Statistics

Rick Wicklin, PhD, is a distinguished researcher in computational statistics at SAS and is a principal developer of SAS/IML software. His areas of expertise include computational statistics, simulation, statistical graphics, and modern methods in statistical data analysis. Rick is author of the books Statistical Programming with SAS/IML Software and Simulating Data with SAS.

11 Comments

  1. Pingback: Automating the Great Christmas Gift Exchange - The DO Loop

  2. Ankur biswas on

    Dear Rick Wicklin Sir,
    I'am pursuing Ph.D. in Agricultural Statistics from Indian Agricultural research Institute, New Delhi, India. I've read your blogs. Its encourages me to learn sas. Now-a-days i am trying to solve the pi i and pi ij for PPSwor scheme for any size of sample from a population of size N.
    For that I need the probabilities of all possible samples (or permutations) and that has to be summed up. I can get that for small sample sizes. But for large sample sizes the permutations becomes so bigger.
    Please help me.
    With regards,

    Reply
      • Ankur biswas on

        Actually I need to get all possible samples (permutations) of size n from a population of size N. For that all possible permutations of n symbols from N symbols are to be generated. But i don't need all permutations as a complete dataset. At the time of permutation generation, for each permutation i need a function of that permutation and that has to be summed up for all the permutations. Actually memory allocation problem arises at the time of permutation generation. The helpful programs shown in all of your blogs writes each permutation to a dataset.
        Please help me.
        With regards,

        Reply
        • Rick Wicklin
          Rick Wicklin on

          I regret that I cannot offer personal assistance. For up to N<=18, you can look at the ALLPERM function in the DATA step. No computer can possibly generate all permutations for even modest values of N. Factorials grow really fast: 60! = 10^80 and even the world's fastest computer can only manage 10^16 computations per second. At that rate, it would require 10^64 seconds to compute all permutations, which is much longer than the age of the universe.

          Reply
          • Ankur biswas on

            Thanks for your suggestion. I've already done it for N=25 using a combination of allcomb and allperm functions. But I need it for N=100. That's the problem. But if we don't store the whole permutation in a dataset and at the time of each permutation generation, if a function of that permutation is calculated and summed to a variables.

            Is it possible? Then only my problem would be solved.
            With regards,

  3. SASIML on

    Dear Rick Wicklin Sir,
    Right now I am working on my Bachelor's thesis and encounter some problems with using IML.

    I'm working on financial data, and trying to develop universe return and cumulative return of benchmark using IML/Macro.

    %let month = 5;
%let startmonth = 5;
%let endmonth = 5;
%let startyear = 1999;
%let endyear = 1999;
%let numyears = %eval(&endyear-&startyear+1);  
%let nummonths = %eval(&endmonth-&startmonth+1);
 
%macro byyear;
%do k = &startyear %to &endyear %by 1;
	data t&k; 
		set toydata;
		where year=&k and month=&month;
	run;
	/*calculation*/	
	ods output avg_return&k = Areturn&k;
	proc iml;
		/*  Set up array for the Chloe Matrix using &numyears for an array factor */
		/*  The allocaiton for j is nummonths, and the allocaiton for i is numyears*/
		/*  i is number of rown = years, and j is the portfolio, i.e., month      */
		use t&k;
		read all into a;
		return&k = a[,2];
		weight&k = 1/ nRow(return&k);
 
		nonMissing = loc(return&k ^=.);
		if ncol(nonMissing)=0 then mean = .;
		else do;
			return&k= return&k[nonMissing,];
			avg_return&k= sum(return&k*weight&k);
		end;
		/*  chloe(i,j) = avg_return&k */
		print avg_return&k;
	quit;
%end;
%mend byyear;
%byyear;

    I am able to get the value, 'avg_return&k.'After getting the avg_return&k, I want to put this value into another vector/array, to make it look like

             Jan       Feb  
1999 1.277      0.22
2000 0.988        ...

    something looks like this. Would you be able to give me some recommendation?

    Your book helped me a lot for my research. Thank you very much.
    Sincerely, Chloe

    Reply

  4. Pingback: Generate permutations in SAS - The DO Loop

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