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dc.contributor.authorBaddeley, Adrian
dc.contributor.authorJammalamadaka, A.
dc.contributor.authorNair, G.
dc.date.accessioned2017-01-30T13:47:29Z
dc.date.available2017-01-30T13:47:29Z
dc.date.created2015-10-29T04:09:49Z
dc.date.issued2014
dc.identifier.citationBaddeley, A. and Jammalamadaka, A. and Nair, G. 2014. Multitype point process analysis of spines on the dendrite network of a neuron. Journal of the Royal Statistical Society. Series C: Applied Statistics. 63 (5): pp. 673-694.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/35067
dc.identifier.doi10.1111/rssc.12054
dc.description.abstract

© 2014 Royal Statistical Society. We develop methods for analysing the spatial pattern of events, classified into several types, that occur on a network of lines. The motivation is the study of small protrusions called 'spines' which occur on the dendrite network of a neuron. The spatially varying density of spines is modelled by using relative distributions and regression trees. Spatial correlations are investigated by using counterparts of the K-function and pair correlation function, where the main problem is to compensate for the network geometry. This application illustrates the need for careful analysis of spatial variation in the intensity of points, before assessing any evidence of clustering.

dc.publisherWILEY-BLACKWELL
dc.titleMultitype point process analysis of spines on the dendrite network of a neuron
dc.typeJournal Article
dcterms.source.volume63
dcterms.source.number5
dcterms.source.startPage673
dcterms.source.endPage694
dcterms.source.issn0035-9254
dcterms.source.titleJournal of the Royal Statistical Society. Series C: Applied Statistics
curtin.departmentDepartment of Mathematics and Statistics
curtin.accessStatusFulltext not available


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