Tom Nielsen | 9 Jul 13:53 2013
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Probabilistic functional programming with Baysig/BayesHive

Dear cafe,

I would like to announce that the Baysig programming language and the
BayesHive analytics environment (http://bayeshive.com) are now
available for beta testers.

Baysig is a new probabilistic, functional and typed programming
language that attempts to realise the vision of "fully Bayesian
computing". That is, in Baysig almost all the work in data processing
consists of building a probabilistic model of the incoming data.
Almost everything else -- optimal decisions, categorisation, measuring
hidden parameters or states, forecasting, testing hypothesis --
becomes trivial. This paradigm can in principle be applied to a large
number of domains, although for the moment we are focusing on models
that are based on continuous parameters. It will therefore be of
interest to users of statistics and dynamical systems models,
including in finance, physics and life sciences.

To analyse data in Baysig, you write a program in the random-number
supply monad that generates simulated data. A special construct,
"estimate", then applies Bayes' theorem to this program and returns
the probability distribution of the model parameters given observed
data. The "estimate" procedure is difficult to implement in Haskell or
similar languages, which encouraged us to develop a new language.
However, in many respects Baysig should feel like Haskell, and we hope
that Baysig will encourage the Haskell community to experiment with
statistical modelling.

We have built a web-based environment to help users, including those
with little-to-no programming experience, use Baysig, at
(Continue reading)

Jerzy Karczmarczuk | 9 Jul 14:02 2013
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Re: Probabilistic functional programming with Baysig/BayesHive

Le 09/07/2013 13:53, Tom Nielsen a écrit :
> Almost everything else -- optimal decisions, categorisation, (...) --
> becomes trivial.
Optimal decisions "trivial"?
Interesting... And not so frequent...

Jerzy Karczmarczuk

Gmane