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Authors: Adrian Baddeley, Rolf Turner, Jorge Mateu, Andrew Bevan
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Hybrids of Gibbs Point Process Models and Their Implementation
Reference: Vol. 55, Issue 11, Nov 2013
Submitted 2012-09-24, Accepted 2013-04-26
Type: Article
Abstract:

We describe a simple way to construct new statistical models for spatial point pattern data. Taking two or more existing models (finite Gibbs spatial point processes) we multiply the probability densities together and renormalise to obtain a new probability density. We call the resulting model a hybrid. We discuss stochastic properties of hybrids, their statistical implications, statistical inference, computational strategies and software implementation in the R package spatstat. Hybrids are particularly useful for constructing models which exhibit interaction at different spatial scales. The methods are demonstrated on a real data set on human social interaction. Software and data are provided.

Paper: [download]
(1250)
Hybrids of Gibbs Point Process Models and Their Implementation
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Supplements: [download]
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spatstat_1.34-1.tar.gz: R source package
(application/x-gzip, 4.2 MB)
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v55i11.R: R example code from the paper
(application/octet-stream, 12.2 KB)
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pairwise.Rnw: Sweave file for illustrative example (Section 5.1)
(application/octet-stream, 2.3 KB)
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pairwise.pdf: Output of pairwise.Rnw
(application/pdf, 97.7 KB)
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simexpt.Rnw: Sweave file for simulation experiment (Section 10)
(application/octet-stream, 5.8 KB)
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simexpt.pdf: Output of simexpt.Rnw
(application/pdf, 131.5 KB)
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gordon.Rnw: Sweave file for analysis of Gordon Square data (Section 11)
(application/octet-stream, 13.8 KB)
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gordon.pdf: Output of gordon.Rnw
(application/pdf, 439.9 KB)
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Creative Commons License
This work is licensed under the licenses
Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3)
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