Abstract

Dependence concepts are a relatively recent development in multivariate distribution theory. They allow dependence to be incorporated into a problem without requiring specific model assumptions, and define classes of multivariate distributions with useful properties. It is not apparent that related notions have also evolved in the theory and applications of stochastic processes. Multivariate concepts and stochastic process concepts, however, have had no influence on each other. In this paper an overview is presented of the work in stochastic processes that is analogous to multivariate dependence concepts.

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