Hi Konrad, thanks for the link. I know your very nice library and actually use clojure.contrib.monads to implement my probability monad. The two approaches are somewhat complementary to each other. Your monad does exact inference on discrete distributions by running through all possibilities. Mine is sampling based and does approximate inference using MCMC. This makes it feasible to simulate larger discrete models and also continuous distributions can easily be incorporated. In the demos section you can find a Gaussian mixture model demonstrating these features.
Nils On Nov 17, 9:58 pm, Konrad Hinsen <googlegro...@khinsen.fastmail.net> wrote: > There's also this one in clojure-contrib (old, not yet moved to the new > contrib collection): > > > https://github.com/richhickey/clojure-contrib/tree/master/src/main/cl... > > Konrad. -- You received this message because you are subscribed to the Google Groups "Clojure" group. To post to this group, send email to clojure@googlegroups.com Note that posts from new members are moderated - please be patient with your first post. To unsubscribe from this group, send email to clojure+unsubscr...@googlegroups.com For more options, visit this group at http://groups.google.com/group/clojure?hl=en
