A \(J\)-function for inhomogeneous point processes

DOI10.1111/j.1467-9574.2011.00482.xMaRDI QIDQ6573448

M. N. M. van Lieshout

Publication date: 16 July 2024

Published in: Statistica Neerlandica (Search for Journal in Brave)

zbMATH Keywords

inhomogeneitymarked point processgenerating functionalconditional intensityspatial interaction\(J\)-functionintensity-reweighted moment stationarityreduced second moment measureproduct densityempty space functionminus sampling estimatorspherical palm contact distribution function

Mathematics Subject Classification ID

Inference from stochastic processes (62Mxx) Multivariate analysis (62Hxx) Stochastic processes (60Gxx)

Cites Work

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• Positively correlated normal variables are associated
• An introduction to the theory of point processes
• A \(J\)-function for marked point patterns
• Nonparametric Measures of Association between a Spatial Point Process and a Random Set, with Geological Applications
• Handbook of Spatial Statistics
• Integral and Differential Characterizations of the GIBBS Process
• Log Gaussian Cox Processes
• A Remark on the Van Lieshout and Baddeley J-Function for Point Processes
• A nonparametric measure of spatial interaction in point patterns
• Estimating the J function without edge correction
• Non‐ and semi‐parametric estimation of interaction in inhomogeneous point patterns
• Markov Point Processes and Their Applications
• A Comparative Study on the Power of van Lieshout and Baddeley's J-Function
• Indices of Dependence Between Types in Multivariate Point Patterns
• Statistical Analysis and Modelling of Spatial Point Patterns
• The conditional intensity of general point processes and an application to line processes
• Second-order analysis of inhomogeneous spatio-temporal point process data

Related Items (5)

Point pattern analysis on a region of a sphere ⋮ Directional analysis for point patterns on linear networks ⋮ Intensity estimation for inhomogeneous Gibbs point process with covariates-dependent chemical activity ⋮ Cox processes driven by transformed Gaussian processes on linear networks -- a review and new contributions ⋮ Spatio-temporal classification in point patterns under the presence of clutter

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