Open Access
February 2018 Local block bootstrap for inhomogeneous Poisson marked point processes
William Garner, Dimitris N. Politis
Bernoulli 24(1): 592-615 (February 2018). DOI: 10.3150/16-BEJ889


The asymptotic theory for the sample mean of a marked point process in $d$ dimensions is established, allowing for the possibility that the underlying Poisson point process is inhomogeneous. A novel local block bootstrap method for resampling inhomogeneous Poisson marked point processes is introduced, and its consistency is proven for the sample mean and related statistics. Finite-sample simulations are carried out to complement the asymptotic results, and demonstrate the feasibility of the proposed methodology.


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William Garner. Dimitris N. Politis. "Local block bootstrap for inhomogeneous Poisson marked point processes." Bernoulli 24 (1) 592 - 615, February 2018.


Received: 1 November 2015; Revised: 1 May 2016; Published: February 2018
First available in Project Euclid: 27 July 2017

MathSciNet: MR3706770
zbMATH: 1381.60091
Digital Object Identifier: 10.3150/16-BEJ889

Keywords: Resampling , sample mean , Stochastic processes

Rights: Copyright © 2018 Bernoulli Society for Mathematical Statistics and Probability

Vol.24 • No. 1 • February 2018
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