Stable Local Computation with Conditional Gaussian Distributions (1999)
| Venue: | Statistics and Computing |
| Citations: | 48 - 0 self |
BibTeX
@ARTICLE{Lauritzen99stablelocal,
author = {Steffen L. Lauritzen and Frank Jensen},
title = {Stable Local Computation with Conditional Gaussian Distributions},
journal = {Statistics and Computing},
year = {1999},
volume = {11},
pages = {191--203}
}
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Abstract
: This article describes a propagation scheme for Bayesian networks with conditional Gaussian distributions that does not have the numerical weaknesses of the scheme derived in Lauritzen (1992). The propagation architecture is that of Lauritzen and Spiegelhalter (1988). In addition to the means and variances provided by the previous algorithm, the new propagation scheme yields full local marginal distributions. The new scheme also handles linear deterministic relationships between continuous variables in the network specification. The new propagation scheme is in many ways faster and simpler than previous schemes and the method has been implemented in the most recent version of the HUGIN software. Key words: Artificial intelligence, Bayesian networks, CG distributions, Gaussian mixtures, probabilistic expert systems, propagation of evidence. 1 Introduction Bayesian networks have developed into an important tool for building systems for decision support in environments characterized by...
