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From Ted Dunning <>
Subject Re: [math] Generate random data using the Inverse CDF Method?
Date Tue, 27 Oct 2009 00:57:06 GMT
I think that the implementations with specialized generators should just
over-ride the generic generator and do the specialized operation.

I have seen cases where _developers_ think there should be multiple
implementations of random number generators, but I don't think I have ever
seen a case where _users_ think that there should be such.

The only reasonable exception I can think of is in test cases.  There I can
imagine that it would be possible to need to say "what *if* I really did get
this sequence of numbers".  That can generally be handled by mocking and
doesn't motivate me to want to make the user experience more complex than it
needs to be.

As the best case in point, does R provide more than one way to generate
exponential deviates?  (no)  Does SPSS? (no)  Does SAS? (don't think so)
Matlab?  (nope)

Why should we?

On Mon, Oct 26, 2009 at 5:33 PM, Mikkel Meyer Andersen <> wrote:

> If we were to put a generator in the distributions (for supporting the
> specialised generators), should this method then just be parameterised
> by a RandomGenerator? Or what would be a proper approach?

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