Bayes linear covariance matrix adjustment for multivariate dynamic linear models

Details Bayes linear covariance matrix adjustment for multivariate dynamic linear models Bayes linear covariance matrix adjustment for multivariate dynamic linear models

1995-06-05

arxiv.org/abs/bayes-an/9506002v1

Physics

Data Analysis, Statistics and Probability

In submission. LaTeX, 17 pages, Chicago BIB-style (included). Also available as a postscript file from http://fourier.dur.ac

Scientific paper

A methodology is developed for the 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. To illustrate the methods, a simple model is developed for a time series representing sales of certain brands of a product from a cash-and-carry depot. The covariance structure underlying the model is revised, and the benefits of this revision on first order inferences are then examined.

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