Re: Generalised bisection
- From
- Ealdwulf Wuffinga <ealdwulf@googlemail.com>
- Date
- Mar 13, 2009, 12:49 UTC
- Message-ID
- <efe2b6d70903130549m63ae9bdeg1cd3f24a43b3e66f@mail.gmail.com>
- In-Reply-To
- <d9c1caea0903121102y5452603fua0e7a1b82e121b01@mail.gmail.com>
On Thu, Mar 12, 2009 at 6:02 PM, Steven Tweed <orthochronous@gmail.com> wrote:
Show 9 quoted lines
> I haven't even looked at the source code so a description of the > mathematical algorithm would help, but I'll just point out that > underflow (in the case of working with probabilities) and overflow > (when working with their negated logarithms) is inherent in most > multi-step Bayesian algorithms. The only solution is to rescale things > as you go so that things stay in a "computable" range. (You're almost > never interested in absolute probabilities anyway but rather relative > probabilities or, in extreme cases, just the biggest probability, so > rescaling isn't losing any useful information.)
Are you sure you aren't thinking of when you are using fixed point? I was under the impression that Bayesian algorithms usually worked okay in floating point.
One issue in BBChop which should be easy to fix, is that I use a dumb way of calculating Beta functions. These are ratios of factorials, so the subexpressions get stupidly big very quickly. But I don't think that is the only problem.
Ealdwulf