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We provide a streamlined proof and improved estimates for the weak multivariate Gnedenko law of large numbers on concentration of random polytopes within the space of convex bodies (in a fixed or a high dimensional setting), as well as a…

Probability · Mathematics 2014-03-11 Daniel J. Fresen , Richard A. Vitale

Let $X_1,\ldots,X_n$ be a sequence of independent random points in $\mathbb{R}^d$ with common Lebesgue density $f$. Under some conditions on $f$, we obtain a Poisson limit theorem, as $n \to \infty$, for the number of large probability…

Probability · Mathematics 2021-05-04 Nicolas Chenavier , Norbert Henze , Moritz Otto

We study the computational complexity of determining the Hausdorff distance of two polytopes given in halfspace- or vertex-presentation in arbitrary dimension. Subsequently, a matching problem is investigated where a convex body is allowed…

Computational Geometry · Computer Science 2014-01-08 Stefan König

In this paper, we give an overview of some results concerning best and random approximation of convex bodies by polytopes. We explain how both are linked and see that random approximation is almost as good as best approximation.

Metric Geometry · Mathematics 2021-11-16 Joscha Prochno , Carsten Schütt , Elisabeth M. Werner

We investigate the asymptotic best approximation of a smooth, strictly convex body $K$ in $\mathbb{R}^d$ by inscribed polytopes with a restricted number of vertices under the intrinsic volume difference. We prove rigidity phenomena in both…

Metric Geometry · Mathematics 2026-02-24 Steven Hoehner

A popular class of problem in statistics deals with estimating the support of a density from $n$ observations drawn at random from a $d$-dimensional distribution. The one-dimensional case reduces to estimating the end points of a univariate…

Statistics Theory · Mathematics 2018-04-27 Victor-Emmanuel Brunel , Jason M. Klusowski , Dana Yang

Let $\mu$ be a probability distribution on $\mathbb{R}^d$ which assigns measure zero to every hyperplane and $S$ a set of points sampled independently from $\mu$. What can be said about the expected combinatorial structure of the convex…

Probability · Mathematics 2023-07-13 Brett Leroux

Let $x_1,\ldots ,x_N$ be independent random points distributed according to an isotropic log-concave measure $\mu $ on ${\mathbb R}^n$, and consider the random polytope $$K_N:={\rm conv}\{ \pm x_1,\ldots ,\pm x_N\}.$$ We provide sharp…

Metric Geometry · Mathematics 2016-01-12 Apostolos Giannopoulos , Labrini Hioni , Antonis Tsolomitis

Let $X_1, \ldots, X_n$ be independent random points drawn from an absolutely continuous probability measure with density $f$ in $\mathbb{R}^d$. Under mild conditions on $f$, we derive a Poisson limit theorem for the number of large…

Probability · Mathematics 2018-11-20 László Györfi , Norbert Henze , Harro Walk

We examine how the measure and the number of vertices of the convex hull of a random sample of $n$ points from an arbitrary probability measure in $\mathbf{R}^d$ relates to the wet part of that measure. This extends classical results for…

Probability · Mathematics 2020-10-13 Imre Bárány , Matthieu Fradelizi , Xavier Goaoc , Alfredo Hubard , Günter Rote

We consider convex hulls of random walks whose steps belong to the domain of attraction of a stable law in $\mathbb{R}^d$. We prove convergence of the convex hull in the space of all convex and compact subsets of $\mathbb{R}^d$, equipped…

Probability · Mathematics 2022-02-28 Wojciech Cygan , Nikola Sandrić , Stjepan Šebek

Approximating convex bodies is a fundamental problem in geometry. Given a convex body $K$ in $\mathbb{R}^d$ for a fixed dimension $d$, the objective is to minimize the number of facets of an approximating polytope for a given Hausdorff…

Computational Geometry · Computer Science 2026-01-26 Sunil Arya , Guilherme D. da Fonseca , David M. Mount

We study the problem of reconstructing a convex body using only a finite number of measurements of outer normal vectors. More precisely, we suppose that the normal vectors are measured at independent random locations uniformly distributed…

Computational Geometry · Computer Science 2014-02-21 Hiba Abdallah , Quentin Mérigot

Let $A$ be a compact $d$-dimensional $C^2$ Riemannian manifold with boundary, embedded in ${\bf R}^m$ where $m \geq d \geq 2$, and let $B$ be a nice subset of $A$ (possibly $B=A$). Let $X_1,X_2, \ldots $ be independent random uniform points…

Probability · Mathematics 2025-09-24 Mathew D. Penrose , Xiaochuan Yang

Polyhedral-type approximations of convex-like domains in $\mathbb{C}^d$ have been considered recently by the second author. In particular, the decay rate of the error in optimal volume approximation as a function of the number of facets has…

Probability · Mathematics 2022-03-24 Siva Athreya , Purvi Gupta , D. Yogeshwaran

For a fixed $k\in\{1,\dots,d\}$ consider random vectors $X_0,\dots, X_{k}\in\mathbb R^d$ with an arbitrary spherically symmetric joint density function. Let $A$ be any non-singular $d\times d$ matrix. We show that the $k$-dimensional volume…

Probability · Mathematics 2019-08-08 Friedrich Götze , Anna Gusakova , Dmitry Zaporozhets

Given a random sample of points from some unknown density, we propose a data-driven method for estimating density level sets under the r-convexity assumption. This shape condition generalizes the convexity property. However, the main…

Statistics Theory · Mathematics 2019-05-09 Alberto Rodríguez-Casal , Paula Saavedra-Nieves

In this paper we partially resolve Hall's conjecture about the distribution of random triangles. We consider the probability that three points chosen uniformly at random, in a bounded convex region of the plane, form an acute triangle.…

Probability · Mathematics 2019-06-21 Gabriel Khan

We prove a randomized version of the generalized Urysohn inequality relating mean-width to the other intrinsic volumes. To do this, we introduce a stochastic approximation procedure that sees each convex body K as the limit of intersections…

Metric Geometry · Mathematics 2016-06-30 Grigoris Paouris , Peter Pivovarov

Consider the random polytope, that is given by the convex hull of a Poisson point process on a smooth convex body in $\mathbb{R}^d$. We prove central limit theorems for continuous motion invariant valuations including the Will's functional…

Probability · Mathematics 2019-04-02 Jens Grygierek