Modeling conditional distributions of continuous variables in Bayesian networks

Abstract

The MTE (mixture of truncated exponentials) model was introduced as a general solution to the problem of specifying conditional distributions for continuous variables in Bayesian networks, especially as an alternative to discretization. In this paper we compare the behavior of two different approaches for constructing conditional MTE models in an example taken from Finance, which is a domain were uncertain variables commonly have continuous conditional distributions. © Springer-Verlag Berlin Heidelberg 2005.