Limit theory for Lipschitz-localized statistics in random geometric models

Fuente: arXiv
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Main Authors: Błaszczyszyn, B., Yogeshwaran, D., Yukich, J. E.
Format: Preprint
Published: 2026
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author Błaszczyszyn, B.
Yogeshwaran, D.
Yukich, J. E.
author_facet Błaszczyszyn, B.
Yogeshwaran, D.
Yukich, J. E.
contents We study sums of locally dependent scores associated with general marked (i.e., labeled) Euclidean point processes. We introduce geometric mixing conditions on the underlying point process and a Lipschitz-"localization" condition on the scores, which jointly ensure a central limit theorem for the sums of the scores as well as expectation and variance asymptotics. Our localization condition is formulated using the bounded Lipschitz metric, providing a distributional criterion. This stands in contrast to the classical stabilization conditions in stochastic geometry, which are typically based on stopping-set constructions. To demonstrate the applicability of our general framework, we consider several stochastic processes indexed by spatial random graphs. These include spin systems, interacting diffusions, and interacting particle systems. In particular, spin systems highlight the importance of our localization condition. Additional applications include empirical random fields and geostatistical Boolean models.
format Preprint
id arxiv_https___arxiv_org_abs_2605_28430
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Limit theory for Lipschitz-localized statistics in random geometric models
Błaszczyszyn, B.
Yogeshwaran, D.
Yukich, J. E.
Probability
Primary 60D05, 60F05, 60G55, Secondary 60K35, 60J76, 82B20, 60G60, 62M30
We study sums of locally dependent scores associated with general marked (i.e., labeled) Euclidean point processes. We introduce geometric mixing conditions on the underlying point process and a Lipschitz-"localization" condition on the scores, which jointly ensure a central limit theorem for the sums of the scores as well as expectation and variance asymptotics. Our localization condition is formulated using the bounded Lipschitz metric, providing a distributional criterion. This stands in contrast to the classical stabilization conditions in stochastic geometry, which are typically based on stopping-set constructions. To demonstrate the applicability of our general framework, we consider several stochastic processes indexed by spatial random graphs. These include spin systems, interacting diffusions, and interacting particle systems. In particular, spin systems highlight the importance of our localization condition. Additional applications include empirical random fields and geostatistical Boolean models.
title Limit theory for Lipschitz-localized statistics in random geometric models
topic Probability
Primary 60D05, 60F05, 60G55, Secondary 60K35, 60J76, 82B20, 60G60, 62M30
url https://arxiv.org/abs/2605.28430