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R vs. Bugs

2 messages · Peter Muhlberger, Brian Ripley

Original
Peter Muhlberger
# 
A naive question from a non-statistician:  I'm looking into running a
Bayesian analysis of a model with high dimensionality.  It's not a
standard model (the likelihood requires a lot of code to implement),
and I'm using a Linux machine.  Was wondering if someone
has any thoughts on what the advantages of OpenBugs are as
opposed to just R (or should I be thinking WinBUGS under Wine?)?  The
AMCMC package in R promises to run MCMC's very rapidly.  Have read
that OpenBugs as a project was 'stalling' in 2007.

Peter
Brian Ripley
# 
Your request is too vague for us to be very helpful.  However OpenBUGS 
runs without very frequent crashes only on some ix86 Linux machines -- and 
what those are is unclear and Uwe Ligges and I (working on BRugs) have 
been unable to find one recently.

There are dozens of Bayesian MCMC packages on CRAN (look at its Bayesian 
task view).  Most are less general and faster than BUGS.

There is no 'AMCMC package in R'.  There is at least one third-party 
effort of that name, not on CRAN and explicitly claiming

    The R function amcmc() will tend to run rather _slowly_,

(his emphasis) so perhaps that is not the one you mean.
On Sun, 22 Jun 2008, Peter Muhlberg wrote:

            

      
      
      
    

        
'code' in what language?  Note that MCMC does *not* require the likelihood 
to be calculated, and its renaissance in statistics ca 30 years ago was 
for models for which the likelihood is not even known completely.