Path: utzoo!utgpu!news-server.csri.toronto.edu!cs.utexas.edu!usc!ucsd!nosc!manta!north
From: north@manta.NOSC.MIL (Mark H. North)
Newsgroups: comp.lang.pascal
Subject: Re: help on random number generator & t
Summary: Beware of random number generators
Message-ID: <1157@manta.NOSC.MIL>
Date: 25 Jul 90 00:41:51 GMT
References: <23899@adm.BRL.MIL> <13000011@uxh.cso.uiuc.edu>
Organization: Naval Ocean Systems Center, San Diego
Lines: 29




In the first place I wouldn't trust Press, et al since I found them to be
quite confused concerning deconvolution -- perhaps they are not so confused
in other areas, I don't know.

Secondly, I wouldn't trust any canned 'random number generator' without
testing. They usually aren't documented very well so you don't know what
you are getting. And even if you are told what kind of RNG is being used
you don't know if it is being implemented properly. For example, the
multiplicative congruential RNG is one of the best (I have found) but its
performance is dependent on the seed chosen. If the seed is even you can
end up with very short sequences before repeat (as small as 2). There are
other restrictions depending on the generator. The way some implementers
deal with this is by resorting to jiggery-pokery with your seed to force it
to conform to requirements. Unfortunately, by this we have lost all control
of the situation.

There are a number of tests used for RNGs such as the poker test, the run
test, etc. However, the ultimate test for a RNG is in YOUR application.
There is no substitute for sanity checks on what you are getting in your
application. Unfortunately, when a RNG fails to perform in one's particular
use the failure can be quite subtle, so beware. Anyone who blindly uses a
RNG for a serious application is either ignorant or a fool. The best advice
I can give is read and understand Knuth and the references he gives and then
proceed with caution.

Mark