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AndersS
Pyrite | Level 9

Hi!  I am doing some computer experiments with Gumbel random numbers.
1) According to the books and manuals:

          CALL STREAMINIT(2);             X= RAND("GUMBEL", MY, SCALE);
An alternative:   Xi= MY - SCALE*LOG( -LOG(RAND('UNIFORM')));

These two seem to produce results that are identical.
I have used both to produce a lot of random numbers. Works fine. Then I calculated the Mean, StdDev and a lot of quantiles.

 

2) An alternative, when producing many random numbers is the following:    X= MY - SCALE*LOG(-LOG(Step));
where Step is the index in a do-loop. 5Mi values. Then I calculated the Mean, StdDev and a lot of quantiles.
The values are almost the same as above, with very small differences,

Fine - OR?

When I look at the values generated using 2) in some small intervals e.g. around the median the values look very smooth and nice.
When I do the same using the values produced by 1) the values are not at all that smooth, but vary up and down.

Question: Is this described in any paper? Are the values produced in 2) also random numbers.

I would appreciate som comments and advice on this matter.

Best Regards AndersS

 

Anders Sköllermo (Skollermo in English)
1 ACCEPTED SOLUTION

Accepted Solutions
ballardw
Super User

I would expect close values to some extent when driven by a "do loop". The index takes very specific increments, which will limit the resulting output to small changes. That is built into the formula you use.

Look at the behavior of -log(step) by itself. You can see that as your "step" increases the value change of the function result gets smaller:

data junk; 
   do i=1 to 100;
      y= -log(i);
      output;
   end;
run;

proc sgplot;
   scatter x=i y=y;
run;

I would not, personally, call method 2 "random" in any way. It is determined by the value of 3 variables. Plug in the same 3 values you get the same result, hence not random. It may generate a range of values similar to a specific random number distribution but for any of the traditional uses of random values I wouldn't touch that approach, at least not without considerable addition to the code.

View solution in original post

4 REPLIES 4
ballardw
Super User

I would expect close values to some extent when driven by a "do loop". The index takes very specific increments, which will limit the resulting output to small changes. That is built into the formula you use.

Look at the behavior of -log(step) by itself. You can see that as your "step" increases the value change of the function result gets smaller:

data junk; 
   do i=1 to 100;
      y= -log(i);
      output;
   end;
run;

proc sgplot;
   scatter x=i y=y;
run;

I would not, personally, call method 2 "random" in any way. It is determined by the value of 3 variables. Plug in the same 3 values you get the same result, hence not random. It may generate a range of values similar to a specific random number distribution but for any of the traditional uses of random values I wouldn't touch that approach, at least not without considerable addition to the code.

AndersS
Pyrite | Level 9
Hi! Many thanks. I agrere with you. /Br AndersS
Anders Sköllermo (Skollermo in English)
PGStats
Opal | Level 21

to get random numbers with method 2 you would need something like:

%let n=5000000;

array _x{&n.} _temporary_;

if _n_ = 1 then do step = 1 to &n.;
	_X{step} = MY - SCALE*LOG(-LOG(Step));
	end;

do step = 1 to &n.;
	X = _X{rand("integer", &n.)};
	output;
	end;

those would look almost OK, as long as n is large, but wouldn't save any significant CPU resources.

PG
AndersS
Pyrite | Level 9
Hi! I will have a further look into this. /Br AndersS
Anders Sköllermo (Skollermo in English)

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