Hybrids of Gibbs point process models and their implementation

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 hyb...

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Main Authors: Baddeley, Adrian, Turner, R., Mateu, J., Bevan, A.
Format: Journal Article
Published: JOURNAL STATISTICAL SOFTWARE 2013
Online Access:http://hdl.handle.net/20.500.11937/29082
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author Baddeley, Adrian
Turner, R.
Mateu, J.
Bevan, A.
author_facet Baddeley, Adrian
Turner, R.
Mateu, J.
Bevan, A.
author_sort Baddeley, Adrian
building Curtin Institutional Repository
collection Online Access
description 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.
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format Journal Article
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institution Curtin University Malaysia
institution_category Local University
last_indexed 2025-11-14T08:12:55Z
publishDate 2013
publisher JOURNAL STATISTICAL SOFTWARE
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spelling curtin-20.500.11937-290822017-01-30T13:10:15Z Hybrids of Gibbs point process models and their implementation Baddeley, Adrian Turner, R. Mateu, J. Bevan, A. 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. 2013 Journal Article http://hdl.handle.net/20.500.11937/29082 JOURNAL STATISTICAL SOFTWARE restricted
spellingShingle Baddeley, Adrian
Turner, R.
Mateu, J.
Bevan, A.
Hybrids of Gibbs point process models and their implementation
title Hybrids of Gibbs point process models and their implementation
title_full Hybrids of Gibbs point process models and their implementation
title_fullStr Hybrids of Gibbs point process models and their implementation
title_full_unstemmed Hybrids of Gibbs point process models and their implementation
title_short Hybrids of Gibbs point process models and their implementation
title_sort hybrids of gibbs point process models and their implementation
url http://hdl.handle.net/20.500.11937/29082