Message-ID: <b0808fdc0803220410n1b3fbc08k4f837a3355d04096@mail.gmail.com>
Date: 2008-03-22T11:10:24Z
From: Antonio, Fabio Di Narzo
Subject: idea for GSoC: an R package for fitting Bayesian Hierarchical Models
In-Reply-To: <b0808fdc0803210956k5b967d6paa9e572f72482df@mail.gmail.com>
I've put online a temp web page with some more info (and sources):
http://antonio.fabio.googlepages.com/rgs%3Athergibbssampler
Bests,
Antonio.
2008/3/21, Antonio, Fabio Di Narzo <antonio.fabio at gmail.com>:
> Dear R developers,
> these days I'm working on some R code for fitting completely generic
> Bayesian Hierarchical Models in R, a la OpenBUGS and JAGS.
>
> A key feature of OpenBUGS and JAGS is that they automatically build an
> appropriate MCMC sampler from a generic model, specified as a directed
> acyclic graph (DAG).
> The spirit of my (would-be) implementation is instead more focused on
> experimentation and prototyping, i.e. is the user who explicitely
> assign samplers for each model variable after specifying the model.
> The sampler can be chosed in a set of predefined samplers, as well as
> customly specified by the user as an R or C function in a very
> flexible way.
>
> Now I have a prototype scheleton implementation (a bounch of R and C
> files, together with some base testing scripts) which works at decent
> speed (w.r.t. JAGS) on some example models, and I'm writing a
> proof-of-concept, reproducible Sweave file about it, to be published
> online shortly.
>
> What do you think about it in general?
> What do you think about developing an R package of it as a GSoC project?
>
> Best regards,
> Antonio, Fabio Di Narzo.
>