A Generalization of the maximal-spacings in several dimensions and a convexity test
read the original abstract
The notion of maximal-spacing in several dimensions was introduced and studied by Deheuvels (1983) for data uniformly distributed on the unit cube. Later on, Janson (1987) extended the results to data uniformly distributed on any bounded set, and obtained a very fine result, namely, he derived the asymptotic distribution of different maximal-spacings notions. These results have been very useful in many statistical applications. We extend Janson's results to the case where the data are generated from a H\"older continuous density that is bounded from below and whose support is bounded. As an application, we develop a convexity test for the support of a distribution.
This paper has not been read by Pith yet.
Forward citations
Cited by 1 Pith paper
-
Extent of occurrence reconstruction using a new data-driven support estimator
A data-driven estimator for the r-convex support of a distribution achieves the same convergence rates as the convex hull under weaker shape assumptions.
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.