Hi all,
I would like to start to use R's MCMC abilities to compute answers in
Bayesian statistics. I don't have any specific problems in mind yet,
but I would like to be able to compute/sample posterior probabilities
for low-dimensional custom models, as well as handle "standard"
Bayesian cases like linear regression and hierarchical models.
R clearly has a lot of abilities in this area:
http://cran.r-project.org/web/views/Bayesian.html
--enough to be confusing! For instance, there are apparently three
separate interfaces to JAGS, and I'm not even sure I want/need to
interface to JAGS at all.
Can someone please get me started? Are there a handful of "must-have"
packages and software that everyone (who uses MCMC regularly) uses?
Any responses are appreciated,
--
Ben
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
