Open Access
November 2017 Probability approximation of point processes with Papangelou conditional intensity
Giovanni Luca Torrisi
Bernoulli 23(4A): 2210-2256 (November 2017). DOI: 10.3150/16-BEJ808

Abstract

We give general bounds in the Gaussian and Poisson approximations of innovations (or Skorohod integrals) defined on the space of point processes with Papangelou conditional intensity. We apply the general results to Gibbs point processes with pair potential and determinantal point processes. In particular, we provide explicit error bounds and quantitative limit theorems for stationary, inhibitory and finite range Gibbs point processes with pair potential and $\beta$-Ginibre point processes.

Citation

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Giovanni Luca Torrisi. "Probability approximation of point processes with Papangelou conditional intensity." Bernoulli 23 (4A) 2210 - 2256, November 2017. https://doi.org/10.3150/16-BEJ808

Information

Received: 1 April 2015; Revised: 1 January 2016; Published: November 2017
First available in Project Euclid: 9 May 2017

zbMATH: 06778241
MathSciNet: MR3648030
Digital Object Identifier: 10.3150/16-BEJ808

Keywords: Chen–Stein’s method , determinantal point process , Gaussian approximation , Gibbs point process , Ginibre point process , innovation , Papangelou intensity , Poisson approximation , Poisson process , Skorohod integral , Stein’s method

Rights: Copyright © 2017 Bernoulli Society for Mathematical Statistics and Probability

Vol.23 • No. 4A • November 2017
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