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Re : st: Stata vs. SAS (random number generation)


From   Naji <[email protected]>
To   <[email protected]>
Subject   Re : st: Stata vs. SAS (random number generation)
Date   Fri, 08 Apr 2005 16:18:54 +0200

Hi


Here is a link to MARSAGLIA Generator & Diehard battery test
I wonder if 
1) One can transpose C code in order to be used either in SAS/Stata (I don't
know how)
2) if the the same random seed will produce the same Pseudo Random Numbers


http://stat.fsu.edu/pub/diehard/

Hope it helps
Regards
Naji


Le 8/04/05 11:16, ��Joseph Coveney�� <[email protected]> a �crit�:

> JP Azevedo wrote:
> 
> Many thanks you all for the valuable comments and suggestions.
> 
> I did a little bit of more digging, and found out that the references on the
> "pseudo-random number generator" on the Stata 8 manuals and the SAS 5
> manuals are quite different.
> 
> While Stata talks about using George Marsalis (1994) 32-bits pseudo-random
> number generator, SAS actually has two different functions RANUNI [Fishman
> and Moore, 1982] and UNIFORM [Lewis, Goodman and Miller (1969) and Kennedy
> and Gentle (1980)].
> 
> Unfortunately the SAS manuals did not present a section with the full
> references, and the Stata one only said:
> 
> Marsaglia, G (1994). Personal communication
> 
> I would like to know if anyone familiar with this literature could advise me
> how feasible it is to create a compatible pseudo-random number generator
> which would be compatible across these two packages?
> 
> ----------------------------------------------------------------------------
> 
> The Stata user manual does describe the algorithm in detail.  I guess that
> Stata's manual cites the personal communication, because George Marsaglia
> hadn't published his KISS generator at the time.  And apparently it still
> hasn't been formally published:  a recent article* cites his 1999 posting to
> sci.stat.math (which provides C source code and can be found archived at
> www.cs.yorku.ca/~oz/marsaglia-rng.html among other places) to reference the
> KISS generator.
> 
> SAS got slammed several years ago for its random number generator
> ( www.amstat.org/publications/tas/mccull-1.pdf and
> www.amstat.org/publications/tas/mccull.pdf ) primarily because of the
> inadequacy of its period length.  SAS Institute put out a rejoinder of sorts
> ( support.sas.com/rnd/app/papers/statisticalaccuracy.pdf ).  (SAS's JMP
> offering has, however, switched to the Mersenne Twister.)  The Stata manual
> states a period of ca. 2^126 for its generator.  Based upon this
> consideration, if you wanted to use the straightforward method that Timothy
> McKenna suggests, then Stata -> SAS would be the better direction, unless
> SAS has since switched to a modern algorithm in its flagship product as
> well.
> 
> If you wanted a statistical-package-neutral source of numbers to use in this
> way, Professor Marsaglia's DIEHARD site at Florida State University held
> downloadable sets of pseudorandom numbers.  That's gone, but there are
> numerous other Web sites that offer pseudorandom number sets for
> downloading, and a few with natural-origin random number sets.
> 
> Joseph Coveney
> 
> * Philip H.W. Leong, Guanglie Zhang, Dong-U Lee, Wayne Luk and John D.
> Villasenor, A comment on the implementation of the Ziggurat method. _Journal
> of Statistical Software_ Volume 12, Issue 7, February 2005.
> www.jstatsoft.org/counter.php?id=114&url=v12/i07/v12i07.pdf&ct=1
> 
> 
> 
> 
> 
> 
> 
> 
> 
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