Scott functions, their representations on domains, and applications to random sets

TL;DR

This paper extends the theory of random sets and capacities by introducing a Radon measure approach that removes the separability requirement, leading to new characterizations and representations of random sets and Poisson processes.

Contribution

It develops a Radon measure framework for capacities on domains, generalizing previous results that required separability, and introduces exponential valuations for Poisson process representation.

Findings

Radon measure approach avoids separability assumption

Characterization of finite and locally finite random sets

Introduction of exponential valuation for Poisson processes

Abstract

Choquet theorems (1954) on integral representation for capacities are fundamental to probability theory. They inspired a growing body of research into different approaches and generalizations of Choquet's results by many other researchers. Notably Math\'{e}ron's work (1975) on distributions over the space of closed subsets has led to further advancements in the theory of random sets. This paper was inspired by the work of Norberg (1989) who generalized Choquet's results to distributions over domains. While Choquet's original theorems were obtained for locally compact Hausdorff (LCH) spaces, both Math\'{e}ron's and Norberg's depend on the assumption of separability in their application of the Carath\'{e}odory's method. Our Radon measure approach differs from the work of Math\'{e}ron and Norberg, in that it does not require separability. This investigation naturally leads to the introduction of finite and locally finite valuations, which allows us to characterize finite and locally finite random sets in terms of capacities on the class of compact subsets. Finally, the treatment of L\'{e}vy exponent by Math\'{e}ron and Norberg is revisited, and the notion of exponential valuation is proposed for the representation of general Poisson processes.