Logistic regression for spatial Gibbs point processes
Logistic regression for spatial Gibbs point processes
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Author / Creator
Publisher
Oxford: Biometrika Trust, University College London
Journal title
Language
English
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Publication information
Publisher
Oxford: Biometrika Trust, University College London
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Scope and Contents
Contents
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...
Alternative Titles
Full title
Logistic regression for spatial Gibbs point processes
Authors, Artists and Contributors
Author / Creator
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TN_cdi_proquest_journals_1532994409
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_1532994409
Other Identifiers
ISSN
0006-3444
E-ISSN
1464-3510
DOI
10.1093/biomet/ast060
