Path: utzoo!mnetor!uunet!lll-winken!lll-lcc!mordor!sri-spam!ames!hao!gatech!purdue!i.cc.purdue.edu!k.cc.purdue.edu!l.cc.purdue.edu!cik
From: cik@l.cc.purdue.edu (Herman Rubin)
Newsgroups: comp.lang.c
Subject: Re: Random Numbers ...
Message-ID: <691@l.cc.purdue.edu>
Date: 29 Feb 88 21:08:04 GMT
References: <11972@brl-adm.ARPA> <7097@sol.ARPA> <3472@bobkat.UUCP> <709@cresswell.quintus.UUCP>
Organization: Purdue University Statistics Department
Lines: 31
Summary: I did mention reuse of physical random numbers

In article <709@cresswell.quintus.UUCP>, ok@quintus.UUCP (Richard A. O'Keefe) writes:
> In article <690@l.cc.purdue.edu>, cik@l.cc.purdue.edu (Herman Rubin) writes:
> > Second, get some physical random bits.
> > And make sure that all bits are random.
> Um, how *do* you "make sure that all bits are random"?
> Physical random numbers aren't all that simple, either.

I meant that the physical random number should be on a storage device.
I did point out that they might have to be reused.

> Journals like JASA and Applied Statistics seem to be happy with the
> use of pseudo-random numbers in Monte Carlo studies.

I would not trust them.  They may take this attitude because they do not
know that there is a cheap alternative.  About 15 years ago, one of my
colleagues came to me about a simulation problem--his 5% significance
values (known theoretically) were coming out 7%.  Changing the random
numbers to XOR with the a binary version of the RAND numbers solved the
problem.

Many Monte Carlo studies suffer from this and other defects.  One should
always put in checks with directly calculable quantities--are you that
sure that you have not made a programming error?  There are several sets
of physical random numbers available.  Also note that I recommended that
physical and pseudo random numbers be XORed; we only need assume that the
physical random numbers do not have their quirks matching the quirks of 
the pseudo random numbers.  That is a much smaller assumption than saying
the pseudo random numbers' quirks will not affect the simulation.
-- 
Herman Rubin, Dept. of Statistics, Purdue Univ., West Lafayette IN47907
Phone: (317)494-6054
hrubin@l.cc.purdue.edu (ARPA or UUCP) or hrubin@purccvm.bitnet