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dc.contributor.advisorParry, Matthew
dc.contributor.authorLuo, Pei
dc.date.available2018-03-20T23:01:38Z
dc.date.copyright2018
dc.identifier.citationLuo, P. (2018). Semiparametric dispersal kernels in stochastic spatiotemporal epidemic models (Thesis, Master of Science). University of Otago. Retrieved from http://hdl.handle.net/10523/7939en
dc.identifier.urihttp://hdl.handle.net/10523/7939
dc.description.abstractThe dispersal kernel plays a fundamental role in stochastic spatiotemporal epidemic models. By quantifying the rate at which an infectious source infects a susceptible individual in terms of their separation distance, the dispersal kernel is able to account for the observed spatial characteristics of an epidemic. The aim of this thesis is to construct a dispersal kernel which belongs to a semiparametric family. We introduce a new concept called the natural bridge basis in order to build the semiparametrized dispersal kernel. We use data from a citrus canker epidemic in Florida to illustrate and examine our approach. We find features of the semiparametrized dispersal kernel which were not previously evident in parametrized dispersal kernels.
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.publisherUniversity of Otago
dc.rightsAll items in OUR Archive are provided for private study and research purposes and are protected by copyright with all rights reserved unless otherwise indicated.
dc.subjectBayesian statistics
dc.subjectMarkov chain Monte Carlo
dc.subjectSI model
dc.subjectspline method
dc.subjectplant disease
dc.titleSemiparametric dispersal kernels in stochastic spatiotemporal epidemic models
dc.typeThesis
dc.date.updated2018-03-20T22:16:58Z
dc.language.rfc3066en
thesis.degree.disciplineMathematics and Statistics
thesis.degree.nameMaster of Science
thesis.degree.grantorUniversity of Otago
thesis.degree.levelMasters
otago.openaccessOpen
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