🚀 go-pugleaf

Another reference on random number generators and testing of them is
"Statistical Computing" by Kennedy and Gentle published by Marcel
Dekker. There are also more recent articles by Marsaglia which I could
look up if you were really interested.

A common problem with Monte Carlo runs, though, is the choice of seed
rather than the quality of the random number generator. The designers of
random number generators go to a great deal of trouble to get
non-repeating sequences of 2^30 or longer but methods of choosing seeds
usually only give you 10000 different seeds or so. One easy fix for this
is to store the state of the random number generator between program
runs and pick up on the same sequence at the next run. This is the
method used in the S statistical system.
-- 

Doug Bates @ wisconsin
ARPA:	bates@wisc-stat.arpa
	bates@uwisc   (if you have the old host table)
UUCP:	...!{allegra,heurikon,ihnp4,seismo,sfwin,ucbvax,uwm-evax}!uwvax!bates