In mathematics, Vitale's random Brunn–Minkowski inequality is a theorem due to Richard Vitale that generalizes the classical Brunn–Minkowski inequality for compact subsets of n-dimensional Euclidean space Rn to random compact sets.
Statement of the inequality Let X be a random compact set in Rn; that is, a Borel–measurable function from some probability space (Ω, Σ, Pr) to the space of non-empty, compact subsets of Rn equipped with the Hausdorff metric. A random vector V : Ω → Rn is called a selection of X if Pr(V ∈ X) = 1. If K is a non-empty, compact subset of Rn, let
‖ K ‖ = max { ‖ v ‖ R n | v ∈ K } {\displaystyle \|K\|=\max \left\{\left.\|v\|_{\mathbb {R} ^{n}}\right|v\in K\right\}}
and define the set-valued expectation E[X] of X to be
E [ X ] = { E [ V ] | V is a selection of X and E ‖ V ‖ < + ∞ } . {\displaystyle \mathrm {E} [X]=\{\mathrm {E} [V]|V{\mbox{ is a selection of }}X{\mbox{ and }}\mathrm {E} \|V\|<+\infty \}.}
Note that E[X] is a subset of Rn. In this notation, Vitale's random Brunn–Minkowski inequality is that, for any random compact set X with E [ ‖ X ‖ ] < + ∞ {\displaystyle E[\|X\|]<+\infty } ,
( v o l n ( E [ X ] ) ) 1 / n ≥ E [ v o l n ( X ) 1 / n ] , {\displaystyle \left(\mathrm {vol} _{n}\left(\mathrm {E} [X]\right)\right)^{1/n}\geq \mathrm {E} \left[\mathrm {vol} _{n}(X)^{1/n}\right],}
where " v o l n {\displaystyle vol_{n}} " denotes n-dimensional Lebesgue measure.
Relationship to the Brunn–Minkowski inequality If X takes the values (non-empty, compact sets) K and L with probabilities 1 − λ and λ respectively, then Vitale's random Brunn–Minkowski inequality is simply the original Brunn–Minkowski inequality for compact sets.
References Gardner, Richard J. (2002). "The Brunn-Minkowski inequality" (PDF). Bull. Amer. Math. Soc. (N.S.). 39 (3): 355–405 (electronic). doi:10.1090/S0273-0979-02-00941-2. Vitale, Richard A. (1990). "The Brunn-Minkowski inequality for random sets". J. Multivariate Anal. 33 (2): 286–293. doi:10.1016/0047-259X(90)90052-J.
