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Related papers: A note on volume thresholds for random polytopes

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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

The volume is an important attribute of a convex body. In general, it is quite difficult to calculate the exact volume. But in many cases, it suffices to have an approximate value. Volume estimation methods for convex bodies have been…

Computational Geometry · Computer Science 2014-01-03 Cunjing Ge , Feifei Ma , Jian Zhang

Choose n random, independent points in R^d according to a fixed distribution. The convex hull of these points is a random polytope. In some cases, central limit theorems have been proven for the components of f-vectors of random polytopes…

Metric Geometry · Mathematics 2011-09-22 Sang Du , Mark Syvuk

In this paper, we provide explicit lower bounds with respect to some quantities of interest (parameters of the underlying distribution, dimension, geometrical characteristics of the domain, position of the origin, etc.) on the spectral gap…

Functional Analysis · Mathematics 2024-03-27 Michel Bonnefont , Aldéric Joulin

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 $K$ be a convex body in $\R^d$, let $j\in\{1, ..., d-1\}$, and let $\varrho$ be a positive and continuous probability density function with respect to the $(d-1)$-dimensional Hausdorff measure on the boundary $\partial K$ of $K$. Denote…

Metric Geometry · Mathematics 2014-10-07 Károly J. Böröczky , Ferenc Fodor , Daniel Hug

Let $T$ be the triangle in the plane with vertices $(0, 0)$, $(0,1)$ and $(0, 1)$. The convex hull $T_n$ of points $(0, 1)$, $(1, 0)$ and $n$ independent random points uniformly distributed in $T$ is the random convex chain. In this paper…

Probability · Mathematics 2025-10-20 Anna Gusakova , Anna Muranova

Let $X_1,\ldots,X_n$ be a standard normal sample in $\mathbb R^d$. We compute exactly the expected volume of the Gaussian polytope $\mathrm{conv}[X_1,\ldots,X_n]$, the symmetric Gaussian polytope $\mathrm{conv}[\pm X_1,\ldots,\pm X_n]$, and…

Probability · Mathematics 2017-06-27 Zakhar Kabluchko , Dmitry Zaporozhets

In this paper we consider the convex hull of a spherically symmetric sample in $R^d$. Our main contributions are some new asymptotic results for the expectation of the number of vertices, number of facets, area and the volume of the convex…

Probability · Mathematics 2014-12-30 Enkelejd Hashorva

We study the expected value of support functions of random polytopes in a certain direction, where the random polytope is given by independent random vectors uniformly distributed in an isotropic convex body. All results are obtained by an…

Functional Analysis · Mathematics 2012-05-10 David Alonso-Gutierrez , Joscha Prochno

The convex hull $P_{n}$ of a Gaussian sample $X_{1},...,X_{n}$ in $R^{d}$ is a Gaussian polytope. We prove that the expected number of facets $E f_{d-1} (P_n)$ is monotonically increasing in $n$. Furthermore we prove this for random…

Probability · Mathematics 2017-06-27 Mareen Beermann , Matthias Reitzner

Random simplices and more general random convex bodies of dimension $p$ in $\mathbb{R}^n$ with $p\leq n$ are considered, which are generated by random vectors having an elliptical distribution. In the high-dimensional regime, that is, if…

Probability · Mathematics 2023-08-17 Anna Gusakova , Johannes Heiny , Christoph Thäle

We propose a method for estimating a log-concave density on $\mathbb R^d$ from samples, under the assumption that there exists an orthogonal transformation that makes the components of the random vector independent. While log-concave…

Statistics Theory · Mathematics 2024-12-20 Sharvaj Kubal , Christian Campbell , Elina Robeva

Let $\mu$ be a log-concave probability measure on ${\mathbb R}^n$ and for any $N>n$ consider the random polytope $K_N={\rm conv}\{X_1,\ldots ,X_N\}$, where $X_1,X_2,\ldots $ are independent random points in ${\mathbb R}^n$ distributed…

Probability · Mathematics 2023-09-18 Silouanos Brazitikos , Apostolos Giannopoulos , Minas Pafis

In this note we examine the volume of the convex hull of two congruent copies of a convex body in Euclidean $n$-space, under some subsets of the isometry group of the space. We prove inequalities for this volume if the two bodies are…

Metric Geometry · Mathematics 2013-06-19 Ákos G. Horváth , Z. Lángi

We show that the expected value of the mean width of a random polytope generated by $N$ random vectors ($n\leq N\leq e^{\sqrt n}$) uniformly distributed in an isotropic convex body in $\R^n$ is of the order $\sqrt{\log N} L_K$. This…

Functional Analysis · Mathematics 2012-05-29 David Alonso-Gutierrez , Joscha Prochno

The beta polytope $P_{n,d}^\beta$ is the convex hull of $n$ i.i.d. random points distributed in the unit ball of $\mathbb{R}^d$ according to a density proportional to $(1-\lVert{x}\rVert^2)^{\beta}$ if $\beta>-1$ (in particular, $\beta=0$…

Probability · Mathematics 2021-02-03 Gilles Bonnet , Zakhar Kabluchko , Nicola Turchi

Choose $n$ random, independent points in $\R^d$ according to the standard normal distribution. Their convex hull $K_n$ is the {\sl Gaussian random polytope}. We prove that the volume and the number of faces of $K_n$ satisfy the central…

Combinatorics · Mathematics 2007-05-23 I. Barany , V. H. Vu

We consider random polytopes in the $d$-dimensional Euclidean space that are the convex hulls i.i.d. random points selected according to beta-prime distributions. These distributions are rotationally symmetric, heavy-tailed, and their…

Metric Geometry · Mathematics 2026-03-24 Ferenc Fodor , Balázs Grünfelder

This paper develops a unified framework for estimating the volume of a set in $\mathbb{R}^d$ based on observations of points uniformly distributed over the set. The framework applies to all classes of sets satisfying one simple axiom: a…

Statistics Theory · Mathematics 2017-12-22 Nicolai Baldin