Second‐Order Analysis of Inhomogeneous Spatial Point Processes Using Case–Control Data

DOI10.1111/j.1541-0420.2006.00683.xzbMath1134.62081OpenAlexW1979956191WikidataQ31121377 ScholiaQ31121377MaRDI QIDQ5459605

S. Gooding, Virgilio Gómez-Rubio, Patrick E. Brown, Amanda G. Chetwynd, Peter J. Diggle

Publication date: 29 April 2008

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/j.1541-0420.2006.00683.x

zbMATH Keywords

kernel smoothingcase-control studyMonte Carlo testenvironmental epidemiologynonstationary spatial point process

Mathematics Subject Classification ID

Inference from spatial processes (62M30) Applications of statistics to environmental and related topics (62P12) Ecology (92D40)

Related Items (9)

A New Estimation Approach for Combining Epidemiological Data From Multiple Sources ⋮ Substationarity for spatial point processes ⋮ Approximate Bayesian inference for multivariate point pattern analysis in disease mapping ⋮ Contributions of spatial point process modelling to biodiversity theory ⋮ Bootstrap bandwidth selection for the pair correlation function of inhomogeneous spatial point processes ⋮ Estimating second-order characteristics of inhomogeneous spatio-temporal point processes ⋮ Inference for Clustered Inhomogeneous Spatial Point Processes ⋮ Stochastic Quasi-Likelihood for Case-Control Point Pattern Data ⋮ A wavelet-based approach to quantify the anisotropy degree of spatial random point configurations

Uses Software

• spatial

Cites Work

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• An introduction to the theory of point processes
• Assessing goodness of fit of spatially inhomogeneous Poisson processes
• A Kernel Method for Smoothing Point Process Data
• The second-order analysis of stationary point processes
• On Estimating the Reduced Second Moment Measure of a Stationary Spatial Point Process
• Non‐ and semi‐parametric estimation of interaction in inhomogeneous point patterns
• Thin Plate Regression Splines
• Applied Spatial Statistics for Public Health Data
• The spectral analysis of two-dimensional point processes

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