Re: [R] Bayesian Networks with deal

From: Spencer Graves <spencer.graves_at_pdf.com>
Date: Fri 23 Jun 2006 - 02:13:01 EST

          Since I haven't seen a reply to this, I will offer a couple of comments. I've never used "deal", but it sounded interesting, so I thought I'd look at it.

          Have you looked at Susanne G. Bøttcher and Claus Dethlefsen. deal: A Package for Learning Bayesian Networks. Journal of Statistical Software, 8(20), 2003, and the deal reference manual downloadable under "documentation" from "www.math.aau.dk/~dethlef/novo/deal"? If yes and you still would like more help from this listserve, please submit another post including a simple, self-contained example explaining something you've tried and why it doesn't seem to answer your question?   (This is suggested in the posting guide! 'www.R-project.org/posting-guide.html'.)

          This documentation might answer your questions. Even though I've not read them, I will guess potential answers to your two questions, hoping some other reader may disabuse us both of our ignorance:

          From what I saw in the examples, I would guess that "deal" supports two types of distributions: normal and finite (discrete). If so, it does NOT support a Poisson. If it were my problem and I still held that view after reviewing this documentation, I might write to the maintainer [listed with help(package="deal")] and ask him for suggestions. Then if it were sufficiently important, I might think about how I would modify the code to allow for a Poisson.

          Regarding simulations, have you looked at "rnetwork", which provides "simulation of data sets with a given dependency structure"?

	  Hope this helps,
	  Spencer Graves

Carsten Steinhoff wrote:
> Hello,
>
> I want to use R to model a bayesian belief network of frequencies for system
> failiures in various departments of a company.
>
> For the nodes I want to use a poisson-distribution parameterized with expert
> knowledge (e.g. with a gamma prior).
> Then I want to fill in learning-data to improve the initial estimates and
> get some information about possible connections.
> Later I want to simulate dependend random variables from the network
>
> I tryed to use the package "deal" for that task, which is as far as I know
> the best (and only?) R-package for that task.
> But a few questions rose that I could not solve with the documentation:
>
> (1) Is it possible to parameterize the prior distribution (for example
> (dpois(x,lambda=60) directly and non gaussian ?
>
> (2) If I've chosen a structure, can I simulate dependend states that are non
> gausian distributed?
>
> Thank you for any idea!
>
> Regards, Carsten
>
> [[alternative HTML version deleted]]
>
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https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Fri Jun 23 02:31:46 2006

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