Variational estimators for the parameters of Gibbs point process models
Variational estimators for the parameters of Gibbs point process models
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International Statistical Institute and Bernoulli Society for Mathematical Statistics and Probability
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English
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Publisher
International Statistical Institute and Bernoulli Society for Mathematical Statistics and Probability
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This paper proposes a new estimation technique for fitting parametric Gibbs point process models to a spatial point pattern dataset. The technique is a counterpart, for spatial point processes, of the variational estimators for Markov random fields developed by Almeida and Gidas. The estimator does not require the point process density to be heredi...
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Full title
Variational estimators for the parameters of Gibbs point process models
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TN_cdi_projecteuclid_primary_oai_CULeuclid_euclid_bj_1372251147
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_projecteuclid_primary_oai_CULeuclid_euclid_bj_1372251147
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ISSN
1350-7265
DOI
10.3150/12-BEJ419
