Central limit theorems for empirical product densities of stationary point processes

Lothar Heinrich () and Stella Klein

Statistical Inference for Stochastic Processes, 2014, vol. 17, issue 2, 138 pages

Abstract: We prove the asymptotic normality of kernel estimators of second- and higher-order product densities (and of the pair correlation function) for spatially homogeneous (and isotropic) point processes observed on a sampling window $$W_n$$ W n , which is assumed to expand unboundedly in all directions as $$n \rightarrow \infty \,$$ n → ∞ . We first study the asymptotic behavior of the covariances of the empirical product densities under minimal moment and weak dependence assumptions. The proof of the main results is based on the Brillinger-mixing property of the underlying point process and certain smoothness conditions on the higher-order reduced cumulant measures. Finally, the obtained limit theorems enable us to construct $$\chi ^2$$ χ 2 -goodness-of-fit tests for hypothetical product densities. Copyright Springer Science+Business Media Dordrecht 2014

Keywords: Kernel-type product densities estimators; Empirical pair correlation function; Brillinger-mixing point processes; Reduced cumulant measures; Large domain statistics; $$\chi ^2$$ χ 2 -goodness-of-fit tests; 60G55; 62M30; 60F05; 62G20 (search for similar items in EconPapers)
Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sistpr:v:17:y:2014:i:2:p:121-138

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DOI: 10.1007/s11203-014-9094-5

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