[Rd] idea for GSoC: an R package for fitting Bayesian Hierarchical Models

[Antonio, Fabio Di Narzo]

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.
>