Generalized Limit Theorems For $U$-max Statistics

TL;DR

This paper establishes a universal Weibull limit theorem for U-max statistics on a circle, generalizing previous results and including new examples and broader distribution conditions.

Contribution

It introduces a general limit theorem for U-max statistics on a circle, encompassing many known results as special cases and extending to arbitrary distributions.

Findings

Weibull distribution as the universal limit for U-max statistics.

The limit parameters depend on kernel degree, maximum points, and Hessians.

The theorem applies to various distributions beyond uniform.

Abstract

U-max statistics were introduced by Lao and Mayer in 2008. Instead of averaging the kernel over all possible subsets of the original sample, they considered the maximum of the kernel. Such statistics are natural in stochastic geometry. Examples are the maximal perimeters and areas of polygons and polyhedra formed by random points on a circle, ellipse, etc. The main method to study limit theorems for U-max statistics is a Poisson approximation. In this paper we consider a general class of kernels defined on a circle, and we prove a universal limit theorem with the Weibull distribution as a limit. Its parameters depend on the degree of the kernel, the structure of its points of maximum and the Hessians of the kernel at these points. Almost all limit theorems known so far may be obtained as simple special cases of our general theorem. We also consider several new examples. Moreover, we consider not only the uniform distribution of points but also almost arbitrary distribution on a circle satisfying mild additional conditions.