Complementary Lipschitz continuity results for the distribution of intersections or unions of independent random sets in finite discrete spaces

We prove that intersections and unions of independent random sets in finite spaces achieve a form of Lipschitz continuity. More precisely, given the distribution of a random set Xi, the function mapping any random set distribution to the distribution of its intersection (under independence assumption) with Xi is Lipschitz continuous with unit Lipschitz constant if the space of random set distributions is endowed with a metric defined as the L-k norm distance between inclusion functionals also known as commonalities. Moreover, the function mapping any random set distribution to the distribution of its union (under independence assumption) with Xi is Lipschitz continuous with unit Lipschitz constant if the space of random set distributions is endowed with a metric defined as the Lk norm distance between hitting functionals also known as plausibilities. Using the epistemic random set interpretation of belief functions, we also discuss the ability of these distances to yield conflict measures. All the proofs in this paper are derived in the framework of Dempster-Shafer belief functions. Let alone the discussion on conflict measures, it is straightforward to transcribe the proofs into the general (non necessarily epistemic) random set terminology. (C) 2019 Elsevier Inc. All rights reserved.