Strong convergence of kernel estimators for product densities of absolutely regular point processes

DOI10.1080/10485259708832715zbMath0884.60041OpenAlexW1967195392MaRDI QIDQ4352134

Eckhard Liebscher, Lothar Heinrich

Publication date: 23 March 1998

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

Full work available at URL: https://doi.org/10.1080/10485259708832715

zbMATH Keywords

rates of convergenceuniform strong convergencepair correlation functionabsolute regularitylarge deviation inequalitiesproduct densitykernel-type estimatorestimation variancesecond-order point process

Mathematics Subject Classification ID

Asymptotic properties of nonparametric inference (62G20) Strong limit theorems (60F15) Point processes (e.g., Poisson, Cox, Hawkes processes) (60G55)

Related Items

Central limit theorems for empirical product densities of stationary point processes, A bound of the \(\beta\)-mixing coefficient for point processes in terms of their intensity functions, On estimating the asymptotic variance of stationary point processes, Unnamed Item, Central limit theorem for the integrated squared error of the empirical second-order product density and goodness-of-fit tests for stationary point processes, Kernel estimation of the diameter distribution in boolean models with spherical grains, A Contribution to the Nonparametric Statistics of Particle Systems, A Contribution to the Nonparametric Statistics of Particle Systems

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