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February 2016 Second-order properties and central limit theorems for geometric functionals of Boolean models
Daniel Hug, Günter Last, Matthias Schulte
Ann. Appl. Probab. 26(1): 73-135 (February 2016). DOI: 10.1214/14-AAP1086

Abstract

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 for mean values of $\psi(Z\cap W)$ are available in the literature. The first aim of the present work is to study the asymptotic covariances of general geometric (additive, translation invariant and locally bounded) functionals of $Z\cap W$ for increasing observation window $W$, including convergence rates. Our approach is based on the Fock space representation associated with $\eta$. For the important special case of intrinsic volumes, the asymptotic covariance matrix is shown to be positive definite and can be explicitly expressed in terms of suitable moments of (local) curvature measures in the isotropic case. The second aim of the paper is to prove multivariate central limit theorems including Berry–Esseen bounds. These are based on a general normal approximation result obtained by the Malliavin–Stein method.

Citation

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Daniel Hug. Günter Last. Matthias Schulte. "Second-order properties and central limit theorems for geometric functionals of Boolean models." Ann. Appl. Probab. 26 (1) 73 - 135, February 2016. https://doi.org/10.1214/14-AAP1086

Information

Received: 1 August 2013; Revised: 1 April 2014; Published: February 2016
First available in Project Euclid: 5 January 2016

zbMATH: 1348.60013
MathSciNet: MR3449314
Digital Object Identifier: 10.1214/14-AAP1086

Subjects:
Primary: 60D05
Secondary: 52A22 , 60F05 , 60G55 , 60H07

Keywords: additive functional , Berry–Esseen bound , Boolean model , central limit theorem , Covariance matrix , curvature measure , Fock space representation , integral geometry , intrinsic volume , Malliavin calculus , Wiener–Itô chaos expansion

Rights: Copyright © 2016 Institute of Mathematical Statistics

Vol.26 • No. 1 • February 2016
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