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Propagation of Probabilities, Means and Variances in Mixed Graphical Association Models (1992)
| Venue: | Journal of the American Statistical Association |
| Citations: | 172 - 2 self |
BibTeX
@ARTICLE{Lauritzen92propagationof,
author = {Steffen L. Lauritzen and Steffen L. Lauritzen},
title = {Propagation of Probabilities, Means and Variances in Mixed Graphical Association Models},
journal = {Journal of the American Statistical Association},
year = {1992},
volume = {87},
pages = {1098--1108}
}
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Abstract
A scheme is presented for modelling and local computation of exact probabilities, means and variances for mixed qualitative and quantitative variables. The models assume that the conditional distribution of the quantitative variables, given the qualitative, is multivariate Gaussian. The computational architecture is set up by forming a tree of belief universes, and the calculations are then performed by local message passing between universes. The asymmetry between the quantitative and qualitative variables sets some additional limitations for the specification and propagation structure. Approximate methods when these are not appropriately fulfilled are sketched. Lauritzen and Spiegelhalter (1988) showed how to exploit the local structure in the specification of a discrete probability model for fast and efficient computation, thereby paving the way for exploiting probability based models as parts of realistic systems for planning and decision support. The technique was subsequently imp...
Keyphrases
mixed graphical association model quantitative variable realistic system additional limitation multivariate gaussian efficient computation decision support approximate method conditional distribution discrete probability model computational architecture propagation structure local message local structure exact probability belief universe local computation qualitative variable
