From: Jeremy Bruestle (jeremy.bruestle_at_[hidden])
Date: 2007-12-11 14:25:30
Sounds like you've got a number of good things brewing. I wrote up the beta
distribution mostly out of necessity for a machine learning project I'm
working on (I needed a fast NVIDIA GPU implementation, so I figured I might
as well write the boost c++ one too, since I was using boost for all the
other psudorandom numbers already). I was wondering if you would be
interested in taking the code and bundling it with the other distributions
you've already got, as it sounds like your testing capabilities are better.
As far as testing, I've only done the basics, but things seem alright, with
the possible concern that the range is 0 <= x <= 1 as opposed to 0 < x < 1,
due to limited precision of floating point, esp when for example a is near 0
and b is very large. It's not a problem for my application, but perhaps
someone who knows the IEEE floating point rules better than I could suggest
a fix. At any rate, I'll email you a copy.
On Dec 11, 2007 5:31 AM, Andrew Sutton <asutton_at_[hidden]> wrote:
> > Jeremy Bruestle wrote:
> >> Hello, I have implemented support for the beta distribution for
> >> boost::random. I was wondering who I should send it to for
> >> examination and possible acceptance into boost?
> Interesting. I took a different approach using a couple of gamma
> distributions. Ironically, I'm also using a rejection based technique
> from Cheng in 1977. Go figure. I also got bored and wrote a bunch of
> other random number generators and fixed some of the ones that were a
> little broken in Boost (Gamma and Lognormal). The results are in my
> own little Boost testing ground:
> I've also been slowly adding support for some of the missing
> Boost.Math libraries here:
> The gumbel_distribution is a renamed version of the
> extreme_value_distribution. I renamed since (it looks like) there are
> three types of extreme value distributions (weibull, gumbel, and
> frechet), and also a generalized extreme value distribution.
> I wanted to rename fisher_f to just fisher also, but didn't get
> around to it.
> I also wrote a histogramming program to help generate plots of random
> numbers (using GNUPlot, for example), and comparing some basic stats
> against their theoretical equivalents - you know, just to make sure
> the random numbers look right. It's a great way of catching
> > If you have worked up docs and test cases that are all ready to be
> > merged
> > into the source, then you could also ask for a formal review (not
> > sure if
> > this qualifies for a "fast track" review, but it probably should do
> > for a
> > small addition like this). If accepted you would then be
> > responsible for
> > making all the necessary changes to the SVN codebase and
> > maintaining the
> > beta random-distribution.
> I was waiting to finish out the Math distributions before dumping
> these wholesale into the sandbox. I think it would probably be a good
> idea to compare the implementations, figure out which is "better" -
> i'd probably lean towards the other since it (hopefully) doesn't
> depend on other variates.
> Incidentally, the term "library" is meant to indicate the place where
> you go to get books as opposed to, say, Boost. They're not placing
> any real restrictions on implementations. The article needs to be
> cited in the code or in the documentation (preferably both).
> Andrew Sutton
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