Toby

Thanks a lot for pointing out this to me.

BTW, it seems like that Data _null_ gave me two pieces of code, any one of which alone can do the job, right?

Max

From: toby dunn [mailto:tobydunn@hotmail.com] Sent: December-14-10 11:45 AM To: bbser2009@gmail.com; sas-l@listserv.uga.edu Subject: RE: code, find all combinations

The AllComb family of functions and call routines were released in 9.2. So if your using 9.1.x then you can't access them.

Toby Dunn

"I'm a hell bent 100% Texan til I die"

"Don't touch my Willie, I don't know you that well"

> Date: Tue, 14 Dec 2010 11:40:40 -0500 > From: bbser2009@GMAIL.COM > Subject: Re: code, find all combinations > To: SAS-L@LISTSERV.UGA.EDU > > Data _null_ > > When running your code, I got this error info below (but still get the > desired results). Could you help me fix it? Thanks. > > Max > > > data _null_; > 7 array a[4] (1 2 3 4); > 8 k = 3; > 9 n = dim(a); > 10 do j=1 to comb(n,k); > 11 call allcomb(j,k,of a[*]); > ------- > 251 > ERROR 251-185: The subroutine ALLCOMB is unknown, or cannot be accessed. > Check your spelling. > Either it was not found in the path(s) of executable images, > or there was incorrect or missing subroutine descriptor information. > > -----Original Message----- > From: Data _null_; [mailto:iebupdte@gmail.com] > Sent: December-14-10 7:30 AM > To: bbser2009 > Cc: SAS-L@listserv.uga.edu > Subject: Re: code, find all combinations > > PROC PLAN and ALLCOMB with example like the documentation. RTM... > > proc plan ordered; > factors obs=%sysfunc(comb(4,3)) k=3 of 4 comb; > run; > quit; > > data _null_; > array a[4] (1 2 3 4); > k = 3; > n = dim(a); > do j=1 to comb(n,k); > call allcomb(j,k,of a[*]); > put j 5. +3 @; > do i = 1 to k; > put a[i] 3. @; > end; > put; > end; > run; > > data _null_; > array x[5] $3 ('ant' 'bee' 'cat' 'dog' 'ewe'); > n=dim(x); > k=3; > ncomb=comb(n,k); > do j=1 to ncomb+1; > call allcomb(j, k, of x[*]); > put j 5. +3 x1-x3; > end; > run; > > On Mon, Dec 13, 2010 at 10:33 PM, bbser2009 <bbser2009@gmail.com> wrote: > > I wrote a specific code finding all samples of size 3 from the population > > consisting of 1, 2 ,3, 4. > > The idea is direct: > > First get data set like this, no repeated values in each observation. > > 1 2 3 > > 2 4 3 > > 2 1 3 > > ... > > > > Then bubble-sort each observation from small to big. > > 1 2 3 > > 2 3 4 > > 1 2 3 > > ... > > > > Next by-group observations that are identical with each other. > > 1 2 3 > > 1 2 3 > > ... > > 2 3 4 > > 2 3 4 > > ... > > > > At last, output the last observation of each by-group to get all the > > samples. > > 1 2 3 > > 1 2 4 > > 1 3 4 > > 2 3 4 > > (For code, see bottom) > > > > Apparently this algorithm/code is hard to generalize. > > So I am curious about how people have addressed this issue in a more > general > > way? > > I guessed the general algorithm had to be complicated. > > By any chance, however, does anyone know at least what key ideas lay > behind > > it? > > Any comments are welcome! > > > > Thanks. > > > > Max > > > > *== Get the all non-repeated permutations of 1, 2, 3, 4 ==; > > data permutation(drop=i j k); > > do i=1 to 4; > > do j=1 to 4; > > do k=1 to 4; > > if (i ne j) and (i ne k) and (j ne k) then > > do; > > x1=i; > > x2=j; > > x3=k; > > output; > > end; > > end; > > end; > > end; > > run; > > > > *== Sorting each observation ==; > > data obs_sorting(drop=temp i j); > > set permutation; > > array x{3}; > > do i=1 to 3-1; > > do j=1 to 3-i; > > if x[j+1]<x[j] then > > do; > > temp=x[j]; > > x[j]=x[j+1]; > > x[j+1]=temp; > > end; > > end; > > end; > > run; > > > > *== Get all samples of size 3 ==; > > proc sort data=obs_sorting out=grouping; > > by x1-x3; > > run; > > > > data samples; > > set grouping; > > by x1-x3; > > if last.x3; > > output; > > run; > > > > proc print data=samples; > > run; > >