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In fact, this is a good source of random data. However, because it is a good source, it could easily be bad for MonteCarlo searching. As I've been suggesting in other posts, MonteCarlo searching benefits from uniformdistributed numbers.
But truely random numbers are not statistically garunteed to be uniformly distributed (no, the law of averages does not work that way :) ), and so they cause MonteCarlo searching to converge more slowly (but do not keep it from converging). This is why psuedorandom numbers can, theoretically, be better than truelyrandom numbers, because often they are crafted to be uniformly distributed  statistically. However, it often occurs in practice that pseudorandom numbers are not perfectly statistically uniformly distributed (what a mouthful), and so can easily lead to a misconvergance. Enter Quasirandom numbers. These are uniformlydistributed and have a bias towards nonrepetition. This means that you still get a garunteed convergence and you get it faster (since there would be no clumps in your set). Ok, time to go. Ciao,
In reply to Random source
by gryng

