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dc.contributor.authorBaddeley, Adrian
dc.contributor.authorTurner, R.
dc.contributor.authorMateu, J.
dc.contributor.authorBevan, A.
dc.date.accessioned2017-01-30T13:10:15Z
dc.date.available2017-01-30T13:10:15Z
dc.date.created2015-10-29T04:09:49Z
dc.date.issued2013
dc.identifier.citationBaddeley, A. and Turner, R. and Mateu, J. and Bevan, A. 2013. Hybrids of Gibbs point process models and their implementation. Journal of Statistical Software. 55 (11): pp. 1-43.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/29082
dc.description.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.

dc.publisherJOURNAL STATISTICAL SOFTWARE
dc.titleHybrids of Gibbs point process models and their implementation
dc.typeJournal Article
dcterms.source.volume55
dcterms.source.number11
dcterms.source.startPage1
dcterms.source.endPage43
dcterms.source.issn1548-7660
dcterms.source.titleJournal of Statistical Software
curtin.departmentDepartment of Mathematics and Statistics
curtin.accessStatusFulltext not available


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