Stable local computation with conditional Gaussian distributions

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 (Journal of the American Statistical Association 87: 1098–1108, 1992).The propagation architecture is that of Lauritzen and Spiegelhalter (Journal of the Royal Statistical Society, Series B 50: 157– 224, 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 computations involved in the new propagation scheme are simpler than those in the previous scheme and the method has been implemented in the most recent version of the HUGIN software.

[1]  N. L. Johnson,et al.  Linear Statistical Inference and Its Applications , 1966 .

[2]  Alan J. Mayne,et al.  Generalized Inverse of Matrices and its Applications , 1972 .

[3]  K. S. Banerjee Generalized Inverse of Matrices and Its Applications , 1973 .

[4]  Calyampudi R. Rao,et al.  Linear Statistical Inference and Its Applications. , 1975 .

[5]  Judea Pearl,et al.  Fusion, Propagation, and Structuring in Belief Networks , 1986, Artif. Intell..

[6]  David J. Spiegelhalter,et al.  Local computations with probabilities on graphical structures and their application to expert systems , 1990 .

[7]  Prakash P. Shenoy,et al.  Axioms for probability and belief-function proagation , 1990, UAI.

[8]  Judea Pearl,et al.  Probabilistic reasoning in intelligent systems , 1988 .

[9]  N. Wermuth,et al.  Graphical Models for Associations between Variables, some of which are Qualitative and some Quantitative , 1989 .

[10]  Judea Pearl,et al.  Probabilistic reasoning in intelligent systems - networks of plausible inference , 1991, Morgan Kaufmann series in representation and reasoning.

[11]  Steffen L. Lauritzen,et al.  Bayesian updating in causal probabilistic networks by local computations , 1990 .

[12]  S. Lauritzen Propagation of Probabilities, Means, and Variances in Mixed Graphical Association Models , 1992 .

[13]  Michael I. Jordan Graphical Models , 2003 .

[14]  Anders L. Madsen,et al.  Lazy Propagation in Junction Trees , 1998, UAI.

[15]  David J. Spiegelhalter,et al.  Probabilistic Networks and Expert Systems , 1999, Information Science and Statistics.