I tend to be more concerned with the "apparent randomness" of the results than with the speed of the algorithm.
As a thought experiment, what is the cumulative time difference in a run using the fastest vs the slowest algorithm? A whole minute? A second? A fractional second? Glen wrote: > "Alan Miller" <[EMAIL PROTECTED]> wrote in message >news:<K1Fa8.25709$[EMAIL PROTECTED]>... > > The fastest way to generate random normals and exponentials is to use George > > Marsaglia's ziggurat algorithm. > > I've seen both ziggurat and Monty Python approaches claimed as being > "about the fastest" or "close to the fastest" among reasonably general > algorithms (not restricted to a single distribution), and they are > both nice and easy to understand and reasonably easy to code. > > But in the case of gaussian distributions, which is faster? > > I don't yet have the CACM article on the Monty Python for the gaussian > case, presumably it has some timing information. But maybe I don't > even need to look if the ziggurat approach is faster. I haven't seen > anything which directly discusses how they compare. > > Glen ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ =================================================================
