Bayesian Network Models with Discrete and Continuous Variables

Author:

Cobb Barry R.,Rumí Rafael,Salmerón Antonio

Publisher

Springer Berlin Heidelberg

Reference39 articles.

1. E. Castillo, J. Gutiérrez, A. Hadi, Expert systems and probabilistic network models, Springer-Verlag, New York, 1997.

2. B. Cobb, P. Shenoy, R. Rumí, Approximating probability density functions with mixtures of truncated exponentials, in: Proceedings of Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU-2004), In press, Perugia, Italy, 2004.

3. B. Cobb, P. Shenoy, Inference in hybrid Bayesian networks with mixtures of truncated exponentials, International Journal of Approximate Reasoning, 2006, In press.

4. R. Cowell, A. Dawid, S. Lauritzen, D. Spiegelhalter, Probabilistic Networks and Expert Systems, Series: Statistics for Engineering and Information Science, Springer, 1999.

5. A. Dempster, N. Laird, D. Rubin, Maximun likelihood from incomplete data via the EM algorithm, Journal of the Royal Statistical Society B 39 (1977) 1–38.

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