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Related papers: On convex hull of Gaussian samples

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New results on uniform convergence in probability for expansions of Gaussian random processes using compactly supported wavelets are given. The main result is valid for general classes of nonstationary processes. An application of the…

Probability · Mathematics 2013-08-08 Yuriy Kozachenko , Andriy Olenko , Olga Polosmak

The paper considers the wave equation, with constant or variable coefficients in $\R^n$, with odd $n\geq 3$. We study the asymptotics of the distribution $\mu_t$ of the random solution at time $t\in\R$ as $t\to\infty$. It is assumed that…

Mathematical Physics · Physics 2007-05-23 T. V. Dudnikova , A. I. Komech , N. E. Ratanov , Yu. M. Suhov

Given a bounded operator $T$ on a Banach space $X$, we study the existence of a probability measure $\mu$ on $X$ such that, for many functions $f:X\to\mathbb K$, the sequence $(f+\dots+f\circ T^{n-1})/\sqrt n$ converges in distribution to a…

Functional Analysis · Mathematics 2013-04-10 Frédéric Bayart

Let X be a normed space. A subset A of X is approximately convex if $d(ta+(1-t)b,A) \le 1$ for all $a,b \in A$ and $t \in [0,1]$ where $d(x,A)$ is the distance of $x$ to $A$. Let $\Co(A)$ be the convex hull and $\diam(A)$ the diameter of…

Functional Analysis · Mathematics 2007-05-23 S. J. Dilworth , Ralph Howard , James W. Roberts

This paper studies the convex hull of $d$-dimensional samples i.i.d. generated from spherically symmetric distributions. Specifically, we derive a complete integration formula for the expected facet number of the convex hull. This formula…

Probability · Mathematics 2024-02-16 Feng Zhao , Xinyi Tong , Shao-Lun Huang

We consider nonparametric estimation of a regression function for a situation where precisely measured predictors are used to estimate the regression curve for coarsened, that is, less precise or contaminated predictors. Specifically, while…

Statistics Theory · Mathematics 2008-12-18 Aurore Delaigle , Peter Hall , Hans-Georg Müller

Let $\mu$ be an even Borel probability measure on ${\mathbb R}$. For every $N>n$ consider $N$ independent random vectors $\vec{X}_1,\ldots ,\vec{X}_N$ in ${\mathbb R}^n$, with independent coordinates having distribution $\mu $. We establish…

Probability · Mathematics 2023-09-26 Minas Pafis

We prove two-sided bounds on the expected values of several geometric functionals of the convex hull of Brownian motion in $\mathbb{R}^n$ and their inverse processes. This extends some recent results of McRedmond and Xu (2017),…

Probability · Mathematics 2026-01-28 Hugo Panzo , Evan Socher

Let $K$ be an isotropic symmetric convex body in ${\mathbb R}^n$. We show that a subspace $F\in G_{n,n-k}$ of codimension $k=\gamma n$, where $\gamma\in (1/\sqrt{n},1)$, satisfies $$K\cap F\subseteq \frac{c}{\gamma }\sqrt{n}L_K (B_2^n\cap…

Metric Geometry · Mathematics 2016-09-29 Apostolos Giannopoulos , Labrini Hioni , Antonis Tsolomitis

We consider the Halfin-Whitt diffusion process $X_d(t)$, which is used, for example, as an approximation to the $m$-server $M/M/m$ queue. We use recently obtained integral representations for the transient density $p(x,t)$ of this diffusion…

Probability · Mathematics 2015-05-06 Qiang Zhen , Charles Knessl

We provide upper bounds of the expected Wasserstein distance between a probability measure and its empirical version, generalizing recent results for finite dimensional Euclidean spaces and bounded functional spaces. Such a generalization…

Statistics Theory · Mathematics 2020-01-29 Jing Lei

We revisit the problem of bounding the expected supremum of a canonical Gaussian process indexed by a convex set $T \subset \mathbf{R}^d$. We develop two decompositions for the Gaussian width, based on the geometry of the index set. The…

Probability · Mathematics 2026-03-04 Reese Pathak , Nikita Zhivotovskiy

We investigate contraction of the Wasserstein distances on $\mathbb{R}^d$ under Gaussian smoothing. It is well known that the heat semigroup is exponentially contractive with respect to the Wasserstein distances on manifolds of positive…

Probability · Mathematics 2020-12-15 Hong-Bin Chen , Jonathan Niles-Weed

We consider large non-Hermitian random matrices $X$ with complex, independent, identically distributed centred entries and show that the linear statistics of their eigenvalues are asymptotically Gaussian for test functions having…

Probability · Mathematics 2023-10-16 Giorgio Cipolloni , László Erdős , Dominik Schröder

Let $Z$ be a Boolean model based on a stationary Poisson process $\eta$ of compact, convex particles in Euclidean space ${\mathbb{R}}^d$. Let $W$ denote a compact, convex observation window. For a large class of functionals $\psi$, formulas…

Probability · Mathematics 2016-02-11 Daniel Hug , Günter Last , Matthias Schulte

N. Dolbilin and M. Tanemura studied the convex hulls of finite subsets of the Clifford torus $T$ in $E^4$. They have completely studied the combinatorial structure of the convex hull for a periodic point set. Moreover, there was performed a…

Metric Geometry · Mathematics 2012-11-30 Alexander Magazinov

We study the convex hulls of reachable sets of nonlinear systems with bounded disturbances and uncertain initial conditions. Reachable sets play a critical role in control, but remain notoriously challenging to compute, and existing…

Optimization and Control · Mathematics 2026-04-16 Thomas Lew , Riccardo Bonalli , Marco Pavone

We consider probability measures arising from the Cauchy summation identity for the LLT (Lascoux--Leclerc--Thibon) symmetric polynomials of rank $n \geq 1$. We study the asymptotic behaviour of these measures as one of the two sets of…

Probability · Mathematics 2023-09-13 Amol Aggarwal , Alexei Borodin , Michael Wheeler

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

Let $G$ be a non--linear function of a Gaussian process $\{X_t\}_{t\in\mathbb{Z}}$ with long--range dependence. The resulting process $\{G(X_t)\}_{t\in\mathbb{Z}}$ is not Gaussian when $G$ is not linear. We consider random wavelet…

Probability · Mathematics 2013-11-28 Marianne Clausel , François Roueff , Murad S. Taqqu , Ciprian A. Tudor
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