"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/ =================================================================