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This paper concerns the geometric treatment of graphical models using Bayes linear methods. We introduce Bayes linear separation as a second order generalised conditional independence relation, and Bayes linear graphical models are constructed using this property. A system of interpretive and diagnostic shadings are given, which summarise the analysis over(More)
A methodology is developed for the Bayes linear adjustment of the covariance matrices underlying a multivariate constant time series dynamic linear model. The covariance matrices are embedded in a distribution-free inner-product space of matrix objects which facilitates such adjustment. This approach helps to make the analysis simple, tractable and robust.(More)
This research assumes that a problem-solving method has an applicabdtty condmon which specifies the properties of "good" problem-dependent parameters for the method Such a condition Is used as the basis of a computer program that mechamcally generates good parameters for the method to use in solving the problem Such problem-dependent parameters for a method(More)
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