Quantifying minimal non-collinearity among random points
Abstract
Let denote the largest angle in all the triangles with vertices among the points selected at random in a compact convex subset of with nonempty interior, where . It is shown that the distribution of the random variable , where is a certain positive real number which depends only on the dimension and the shape of , converges to the standard exponential distribution as . By using the Steiner symmetrization, it is also shown that -- which is referred to in the paper as the elongation of -- attains its minimum if and only if is a ball in . Finally, the asymptotics of for large is determined.
Cite
@article{arxiv.1608.04455,
title = {Quantifying minimal non-collinearity among random points},
author = {Iosif Pinelis},
journal= {arXiv preprint arXiv:1608.04455},
year = {2016}
}
Comments
7 pages. Version 2: minor mistakes and typos are fixed. Version 3: it is also shown that the elongation attains its minimum only on balls, and the large-dimension asymptotics of the elongation for balls is determined