[R--gR] Package for Discrete Bayesian Networks
All, Many thanks for your replies. I'm always very interested in exchanging ideas and experience. If I'm not mistaken you can do inference and simulation with gRain. Maybe that solves Thomas' problem. My problem pertains more to structural learning and learning about probabilities. If possible, I would like to use free/open source software. In this sense, I would prefer to avoid software like Hugin. Kevin Murpy has a large collection of Matlab code on his page, see http://www.cs.ubc.ca/~murphyk/Software/index.html He seems to offer it under the Lesser GNU Public License according to http://www.cs.ubc.ca/~murphyk/Software/BDAGL/index.html Has anybody done any work on porting his software somehow to R? Thanks, Matthias
Thomas Liebig wrote:
Hi Matthias, I also want to utilise large discrete Bayesian Networks with R (for spatial applications). Actually I learn the networks outside R with some selfmade tools and am looking for a package that offers me basic inference and sampling functions afterwards. Deal doesnt provide them. Claus Dethlefsen suggested to use Rhugs instead that provides an interface to hugin. Therefore, i'm currently implementing these two R functions (inference, sampling) plus an additional import function. For your application you would also need a fast Network Search algorithm for large networks. Perhaps the 'Sparse Candidate Algorithm', 'Scalable Sparse Bayesian Network Search' or the 'Screen Based Network Search' as deal only provides the poor Greedy Search for Bayesian Networks. Feel free to contact me in case, you are interested in exchanging functions or experience. Your application sounds also very interesting to me, and i would be happy to learn more about your textmining domain. regards, Thomas
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