I would argue the opposite. While I agree with Doug that you need good RNGs (though not necessarily true RNGs) in order to avoid bias, the problem with good pseudo- or true- RNGs is that they have order N^2 convergence for Monte Carlo simulations. Quasi-random number generators on the other hand (such as multiples of an irrational square root, or a Peano tiling) converge in order N. If you can trust the results, faster conergence lets you simulate more. -Roger
On Sat, 21 Jul 2007 23:18:36 -0600, Douglas Roberts <[EMAIL PROTECTED]> wrote: > Simulations of stochastic processes also require good RN generators, > especially for simulations of large systems with (I hate to use this > word) > emergent behavioral properties. A bad RN generator will introduce > emergent > behavior that will be "flavored" by a bad random sequences. > > ============================================================ FRIAM Applied Complexity Group listserv Meets Fridays 9a-11:30 at cafe at St. John's College lectures, archives, unsubscribe, maps at http://www.friam.org
