Intensity Estimation for Spatial Point Processes Observed with Noise

DOI10.1111/j.1467-9469.2007.00583.xzbMath1164.62068OpenAlexW2031716600MaRDI QIDQ3608271

Lionel Cucala

Publication date: 28 February 2009

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

Full work available at URL: https://doi.org/10.1111/j.1467-9469.2007.00583.x

zbMATH Keywords

variancebiasdeconvolutionbandwidth selectionkernel intensity estimatoredge-correction

Mathematics Subject Classification ID

Inference from spatial processes (62M30) Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05) Non-Markovian processes: estimation (62M09)

Related Items (7)

BAYESIAN SELECTION OF LOCAL BANDWIDTH IN NON-HOMOGENEOUS POISSON PROCESS KERNEL ESTIMATORS FOR THE INTENSITY FUNCTION ⋮ On estimation of the intensity function of a point process ⋮ Bayesian Selection of Adaptive Bandwidth in Non-homogeneous Poisson Process Kernel Estimators for the Intensity Function ⋮ Bivariate deconvolution with SIMEX: an application to mapping Alaska earthquake density ⋮ Estimating spatial variation in disease risk from locations coarsened by incomplete geocoding ⋮ Estimating second order characteristics of point processes with known independent noise ⋮ Consistent Smooth Bootstrap Kernel Intensity Estimation for Inhomogeneous Spatial Poisson Point Processes

Cites Work

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• Estimating second order characteristics of point processes with known independent noise
• On the optimal rates of convergence for nonparametric deconvolution problems
• Practical bandwidth selection in deconvolution kernel density estimation
• Density estimation for point processes
• Statistical inference for spatial Poisson processes
• Deconvolving kernel density estimators
• A Kernel Method for Smoothing Point Process Data
• Equivalence of Smoothing Parameter Selectors in Density and Intensity Estimation
• Non-parametric Bayesian Estimation of a Spatial Poisson Intensity
• Data-driven deconvolution
• Models for point processes observed with noise
• Prediction of Spatial Cumulative Distribution Functions Using Subsampling
• Nonparametric regression in the presence of measurement error
• Statistics for Spatial Data

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