Re: Generalised bisection

On Thu, Mar 12, 2009 at 6:02 PM, Steven Tweed [off-list ref] wrote:

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