R help - Jul 2007 - R equivalent to Matlab's Bayes net toolbox

Hi,

I'm attending  summer School at UCLA (IPAM) on "probabilistics models
of
cognition". I have been an R-user since v. 1.4.1, but was trained in the  
frequentist tradition (as most psychologists!). I found that all faculty  
here use matlab and Murphy's bayes net toolbox. I have not had the need to  
use matlab before, and would love to stick to R for graphics models and  
bayesian modeling in general (even if it takes me extra time to cross-code  
the examples in matlab into R).

I'm trying to find an R equivalent to Matlab's Bayes net toolbox.

I have found packages 'deal' and 'gR', and played around with:
http://www.ci.tuwien.ac.at/gR/

But I cannot really figure out how all these packages are integrated.  
Also, appendix B of 'bayesian AI' lists gR as "vaporware"
(although this
could well be outdated by now).

Is there any R news article on bayesian networks? It's hard to find,  
because I don't think the content of R-news is indexed in CRAN. I could  
download every issue and search the TOC, but it'd be time-consuming.

Even though the examples in the documentation in package 'deal' are
good,
they fall short. A good tutorial would be great.
What I'd like to know from you is whether R is a sensible choice or  
whether BNT is just easier and more mature.

Right now I could easily chose R or Matlab, since I have made little  
investment in any form of bayesian networks modeling; However, since I  
have a better background in R than in Matlab, I'd love to stay with R.

Any resources (mailing lists, books, tutorials) would be greatly  
appreciated.

Thanks a lot in advance,
-Jose

-- 
Jose Quesada, PhD.
http://www.andrew.cmu.edu/~jquesada

Jose,
I am not entirely sure what Matlabs Bayes net toolbox does, but I guess it
implements as propagation algorithm for Bayesian networks. There is no such
package on CRAN - yet - but there will be soon: I've created a package
called gRbayesnet which implements the "Lauritzen-Spiegelhalter"
propagation algorithm. I expect to upload it to CRAN within the next few days.
Best regards
S?ren

________________________________

Fra: r-help-bounces at stat.math.ethz.ch p? vegne af Jose Quesada 
Sendt: ma 16-07-2007 17:58
Til: r-help at lists.r-project.org
Emne: [R] R equivalent to Matlab's Bayes net toolbox



Hi,

I'm attending  summer School at UCLA (IPAM) on "probabilistics models
of
cognition". I have been an R-user since v. 1.4.1, but was trained in the 
frequentist tradition (as most psychologists!). I found that all faculty 
here use matlab and Murphy's bayes net toolbox. I have not had the need to 
use matlab before, and would love to stick to R for graphics models and 
bayesian modeling in general (even if it takes me extra time to cross-code 
the examples in matlab into R).

I'm trying to find an R equivalent to Matlab's Bayes net toolbox.

I have found packages 'deal' and 'gR', and played around with:
http://www.ci.tuwien.ac.at/gR/

But I cannot really figure out how all these packages are integrated. 
Also, appendix B of 'bayesian AI' lists gR as "vaporware"
(although this
could well be outdated by now).

Is there any R news article on bayesian networks? It's hard to find, 
because I don't think the content of R-news is indexed in CRAN. I could 
download every issue and search the TOC, but it'd be time-consuming.

Even though the examples in the documentation in package 'deal' are
good,
they fall short. A good tutorial would be great.
What I'd like to know from you is whether R is a sensible choice or 
whether BNT is just easier and more mature.

Right now I could easily chose R or Matlab, since I have made little 
investment in any form of bayesian networks modeling; However, since I 
have a better background in R than in Matlab, I'd love to stay with R.

Any resources (mailing lists, books, tutorials) would be greatly 
appreciated.

Thanks a lot in advance,
-Jose

--
Jose Quesada, PhD.
http://www.andrew.cmu.edu/~jquesada

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