The wrapping hull and a unified framework for volume estimation

Abstract

This paper develops a unified framework for estimating the volume of a set in R d based on observations of points uniformly distributed over the set. The framework applies to all classes of sets satisfying one simple axiom: a class is assumed to be intersection stable. No further hypotheses on the boundary of the set are imposed; in particular, the convex sets and the so-called weakly-convex sets are covered by the framework. The approach rests upon a homogeneous Poisson point process model. We introduce the so-called wrapping hull, a generalization of the convex hull, and prove that it is a sufficient and complete statistic. The proposed estimator of the volume is simply the volume of the wrapping hull scaled with an appropriate factor. It is shown to be consistent for all classes of sets satisfying the axiom and mimics an unbiased estimator with uniformly minimal variance. The construction and proofs hinge upon an interplay between probabilistic and geometric arguments. The tractability of the framework is numerically confirmed in a variety of examples.

Minimax Estimation of the Volume of a Set Under the Rolling Ball Condition

“…In work appearing after ours, Baldin [3] expands on his previous work [4] by considering other classes of sets (including the class considered here) and adopts a sample splitting strategy to correct for the bias.…”