Weak Convergence of Topological Measures

Svetlana V. Butler ()
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Svetlana V. Butler: University of California, Santa Barbara

Journal of Theoretical Probability, 2022, vol. 35, issue 3, 1614-1639

Abstract: Abstract Topological measures and deficient topological measures are defined on open and closed subsets of a topological space, generalize regular Borel measures, and correspond to (nonlinear in general) functionals that are linear on singly generated subalgebras or singly generated cones of functions. They lack subadditivity, and many standard techniques of measure theory and functional analysis do not apply to them. Nevertheless, we show that many classical results of probability theory hold for topological and deficient topological measures. In particular, we prove a version of Aleksandrov’s theorem for equivalent definitions of weak convergence of deficient topological measures. We also prove a version of Prokhorov’s theorem which relates the existence of a weakly convergent subsequence in any sequence in a family of topological measures to the characteristics of being a uniformly bounded in variation and uniformly tight family. We define Prokhorov and Kantorovich–Rubenstein metrics and show that convergence in either of them implies weak convergence of (deficient) topological measures on metric spaces. We also generalize many known results about various dense and nowhere dense subsets of deficient topological measures. The present paper constitutes a necessary step to further research in probability theory and its applications in the context of (deficient) topological measures and corresponding nonlinear functionals.

Keywords: Weak convergence; Topological measure; Aleksandrov’s theorem; Prokhorov’s theorem; Prokhorov and Kantorovich–Rubenstein metrics; Dense subset; 60B10; 60B05; 28A33; 28C15 (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s10959-021-01095-4

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