Compact convex sets of the plane and probability theory

Abstract

The Gauss-Minkowski correspondence in ${\mathbb{R}}^2$ states the existence of a homeomorphism between the probability measures $\mu$ on $[0,2\pi ]$ such that ${\int }_0^{2\pi }{e}^{ix}d\mu (x)=0$ and the compact convex sets (CCS) of the plane with perimeter~1. In this article, we bring out explicit formulas relating the border of a CCS to its probability measure. As a consequence, we show that some natural operations on CCS -- for example, the Minkowski sum -- have natural translations in terms of probability measure operations, and reciprocally, the convolution of measures translates into a new notion of convolution of CCS. Additionally, we give a proof that a polygonal curve associated with a sample of $n$ random variables (satisfying ${\int }_0^{2\pi }{e}^{ix}d\mu (x)=0$) converges to a CCS associated with $\mu$ at speed $\sqrt{n}$, a result much similar to the convergence of the empirical process in statistics. Finally, we employ this correspondence to present models of smooth random CCS and simulations.