Consistent Smooth Bootstrap Kernel Intensity Estimation for Inhomogeneous Spatial Poisson Point Processes

DOI10.1111/sjos.12183zbMath1382.60073OpenAlexW1923009988MaRDI QIDQ2815589

Jorge Mateu, Isabel Fuentes-Santos, Wenceslao González Manteiga

Publication date: 29 June 2016

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

Full work available at URL: https://doi.org/10.1111/sjos.12183

zbMATH Keywords

mean integrated squared errorbandwidth matrixnon-parametric estimationfirst-order intensityinfill asymptotic framework

Mathematics Subject Classification ID

Asymptotic properties of nonparametric inference (62G20) Applications of statistics to environmental and related topics (62P12) Nonparametric estimation (62G05) Nonparametric statistical resampling methods (62G09) Point processes (e.g., Poisson, Cox, Hawkes processes) (60G55)

Related Items (5)

BAYESIAN SELECTION OF LOCAL BANDWIDTH IN NON-HOMOGENEOUS POISSON PROCESS KERNEL ESTIMATORS FOR THE INTENSITY FUNCTION ⋮ Testing similarity between first-order intensities of spatial point processes. A comparative study ⋮ Bootstrap bandwidth selection for the pair correlation function of inhomogeneous spatial point processes ⋮ Infill asymptotics and bandwidth selection for kernel estimators of spatial intensity functions ⋮ Bootstrapping kernel intensity estimation for inhomogeneous point processes with spatial covariates

Uses Software

• spatstat

Cites Work

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