Brillinger mixing of determinantal point processes and statistical applications

DOI10.1214/16-EJS1116zbMath1403.60039arXiv1507.06506MaRDI QIDQ259194

Frédéric Lavancier, Christophe Ange Napoléon Biscio

Publication date: 11 March 2016

Published in: Electronic Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1507.06506

zbMATH Keywords

regularitycentral limit theorempoint processesinhibitionkernel estimatorpair correlation functionintensitymoment measures

Mathematics Subject Classification ID

Asymptotic properties of nonparametric inference (62G20) Central limit and other weak theorems (60F05) Non-Markovian processes: estimation (62M09) Point processes (e.g., Poisson, Cox, Hawkes processes) (60G55)

Related Items (7)

Brillinger-mixing point processes need not to be ergodic ⋮ On the strong Brillinger-mixing property of \(\alpha\)-determinantal point processes and some applications. ⋮ Stationary determinantal processes: \(\psi\)-mixing property and correlation dimensions ⋮ Asymptotic goodness-of-fit tests for point processes based on scaled empirical K-functions ⋮ Mixing properties and central limit theorem for associated point processes ⋮ Contrast Estimation for Parametric Stationary Determinantal Point Processes ⋮ A bound of the \(\beta\)-mixing coefficient for point processes in terms of their intensity functions

Uses Software

• spatstat

Cites Work

• On the strong Brillinger-mixing property of \(\alpha\)-determinantal point processes and some applications.
• Absolute regularity and Brillinger-mixing of stationary point processes
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• Cellular Networks with $$\alpha $$-Ginibre Configurated Base Stations
• On One of Matérn's Hard-core Point Process Models
• Normal convergence of multidimensional shot noise and rates of this convergence
• The coincidence approach to stochastic point processes
• Real Analysis and Probability
• An Introduction to the Theory of Point Processes
• Asymptotic Methods in Statistics of Random Point Processes
• An Introduction to the Theory of Point Processes
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