"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
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