Dear Adam

I know of the following interesting papers:

Steffen L. Lauritzen (1992). Propagation of Probabilities, Means and Variances
in Mixed Graphical Association Models. JASA 87: 1098-1108.

Steffen L. Lauritzen and Frank Jensen (2001). Stable local computation with
conditional Gaussian distributions. Statistics and Computing 11: 191-203.

Some other interesting papers written by C. Raphael can be downloaded from his
homepage:

 http://fafner.math.umass.edu/~raphael/papers/index.html

Learning in Bayesian Networks with mixed variables is treated in

S. G. B�ttcher (2001). Learning Bayesian networks with mixed variables. Artificial
Intelligence and Statistics 2001: 149-156.

Downloadable from
 http://www.ai.mit.edu/conferences/aistats2001/papers.html

Claus Dethlefsen and I have developed a freeware package (DEAL) for use with R,
which implements methods for learning Bayesian networks with mixed variables. See
the webpage:

 http://www.math.auc.dk/novo/deal/

for downloads and installation instructions. The package is still experimental and
all comments are very welcome.

Regards,
Susanne B�ttcher


Adam Sosnowski wrote:

> Hello,
> Can anyone point me to papers on Bayesian networks with both
> continous and discret variables. So far I only found A.Moor work
> on Mix-nets.
>
> Adam Sosnowski
>
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