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Output Category: C1: Journal Article (Schol Refereed Journal)
Strategic Research Area: None
TISI Citations: 8 PlumX StatisticsPlumX Statistics
Scopus Citations: 8
Journal Impact: 1.45
All Authors: Baddeley, A, Coeurjolly, J, Rubak, E, Waagepetersen, R Number: 4
UWA Authors: Baddeley, A. Number: 1
Title: Logistic regression for spatial Gibbs point processes
Journal: BIOMETRIKA   
ISBN/ISSN 0006-3444
Year: 2014
Pages: 377-392
Volume: 101
Issue: 2
Full Reference (Harvard Style): Baddeley, A., Coeurjolly, J., Rubak, E., Waagepetersen, R. 2014, 'Logistic regression for spatial Gibbs point processes', BIOMETRIKA, 101, 2, pp. 377-392.
Abstract:
We propose a computationally efficient technique, based on logistic regression, for fitting Gibbs point process models to spatial point pattern data. The score of the logistic regression is an unbiased estimating function and is closely related to the pseudolikelihood score. Implementation of our technique does not require numerical quadrature, and thus avoids a source of bias inherent in other methods. For stationary processes, we prove that the parameter estimator is strongly consistent and asymptotically normal, and propose a variance estimator. We demonstrate the efficiency and practicability of the method on a real dataset and in a simulation study. © 2014 Biometrika Trust.