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In a $d$-dimensional convex body $K$ random points $X_0, \dots, X_d$ are chosen. Their convex hull is a random simplex. The expected volume of a random simplex is monotone under set inclusion, if $K \subset L$ implies that the expected…

Metric Geometry · Mathematics 2016-06-08 Benjamin Reichenwallner , Matthias Reitzner

In a $d$-dimensional convex body $K$, for $n \leq d+1$, random points $X_0, \dots, X_{n-1}$ are chosen according to the uniform distribution in $K$. Their convex hull is a random $(n-1)$-simplex with probability $1$. We denote its…

Metric Geometry · Mathematics 2017-06-23 Benjamin Reichenwallner

We consider the moments of the volume of the symmetric convex hull of independent random points in an $n$-dimensional symmetric convex body. We calculate explicitly the second and fourth moments for $n$ points when the given body is $B_q^n$…

Metric Geometry · Mathematics 2007-05-23 Mark W. Meckes

The sample range of uniform random points $X_1, \dots , X_n$ chosen in a given convex set is the convex hull ${\rm conv}[X_1, \dots, X_n]$. It is shown that in dimension three the expected volume of the sample range is not monotone with…

Probability · Mathematics 2016-12-07 Stefan Kunis , Benjamin Reichenwallner , Matthias Reitzner

The convex hull of N independent random points chosen on the boundary of a simple polytope in R^n is investigated. Asymptotic formulas for the expected number of vertices and facets, and for the expectation of the volume difference are…

Probability · Mathematics 2022-01-11 M. Reitzner , C. Schuett , E. M. Werner

We study the expected volume of random polytopes generated by taking the convex hull of independent identically distributed points from a given distribution. We show that for log-concave distributions supported on convex bodies, we need at…

Metric Geometry · Mathematics 2021-11-16 Debsoumya Chakraborti , Tomasz Tkocz , Beatrice-Helen Vritsiou

Suppose we choose $N$ points uniformly randomly from a convex body in $d$ dimensions. How large must $N$ be, asymptotically with respect to $d$, so that the convex hull of the points is nearly as large as the convex body itself? It was…

Probability · Mathematics 2020-09-22 Alan Frieze , Wesley Pegden , Tomasz Tkocz

It is known that for a convex body K in R^d of volume one, the expected volume of random simplices in K is minimised if K is an ellipsoid, and for d = 2, maximised if K is a triangle. Here we provide corresponding stability estimates.

Metric Geometry · Mathematics 2010-06-03 Gergely Ambrus , Károly J. Böröczky

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

Let K be a compact convex body in Rd, let Kn be the convex hull of n points chosen uniformly and independently in K, and let fi(Kn) denote the number of i-dimensional faces of Kn. We show that for planar convex sets, E(f0(Kn)) is increasing…

Computational Geometry · Computer Science 2012-11-30 Olivier Devillers , Marc Glisse , Xavier Goaoc , Guillaume Moroz , Matthias Reitzner

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

We prove an exponential deviation inequality for the convex hull of a finite sample of i.i.d. random points with a density supported on an arbitrary convex body in $\R^d$, $d\geq 2$. When the density is uniform, our result yields rate…

Probability · Mathematics 2017-04-07 Victor-Emmanuel Brunel

We show that there is no algorithm which, provided a polynomial number of random points uniformly distributed over a convex body in R^n, can approximate the volume of the body up to a constant factor with high probability.

Probability · Mathematics 2012-11-27 Ronen Eldan

We derive explicit formulae for the expected volume and the expected number of facets of the convex hull of several multidimensional Gaussian random walks in terms of the Gaussian persistence probabilities. Special cases include the already…

Probability · Mathematics 2020-12-25 Julien Randon-Furling , Dmitry Zaporozhets

Let K be a convex body in $R^d$. A random polytope is the convex hull $[x_1,...,x_n]$ of finitely many points chosen at random in K. $\Bbb E(K,n)$ is the expectation of the volume of a random polytope of n randomly chosen points. I.…

Metric Geometry · Mathematics 2016-09-06 Carsten Schütt

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

We consider the convex hull of a finite sample of i.i.d. points uniformly distributed in a convex body in $\R^d$, $d\geq 2$. We prove an exponential deviation inequality, which leads to rate optimal upper bounds on all the moments of the…

Statistics Theory · Mathematics 2013-11-13 Victor-Emmanuel Brunel

Estimating the volume of a convex body is a canonical problem in theoretical computer science. Its study has led to major advances in randomized algorithms, Markov chain theory, and computational geometry. In particular, determining the…

Quantum Physics · Physics 2025-03-05 Arjan Cornelissen , Simon Apers , Sander Gribling

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

Based on observations of points uniformly distributed over a convex set in $\R^d$, a new estimator for the volume of the convex set is proposed. The estimator is minimax optimal and also efficient non-asymptotically: it is nearly unbiased…

Statistics Theory · Mathematics 2016-01-22 Nikolay Baldin , Markus Reiß
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