Multivariate geometric anisotropic Cox
processes |
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Authors: | James S Martin David J Murrell Sofia C Olhede |
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Institution: | 1. Department of Mathematics, Imperial College London, London, UK;2. Centre for Biodiversity and Environment Research, Department of Genetics, Evolution and Environment, University College London, London, UK;3. Institute of Mathematics, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland |
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Abstract: | This paper introduces a new modeling and inference framework for multivariate and anisotropic point processes. Building on recent innovations in multivariate spatial statistics, we propose a new family of multivariate anisotropic random fields, and from them a family of anisotropic point processes. We give conditions that make the proposed models valid. We also propose a Palm likelihood-based inference method for this type of point process, circumventing issues of likelihood tractability. Finally we illustrate the utility of the proposed modeling framework by analyzing spatial ecological observations of plants and trees in the Barro Colorado Island data. |
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Keywords: | forest ecology intractable likelihood multivariate point processes |
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