Show simple item record

Files in this item

Thumbnail

Item metadata

dc.contributor.authorAltieri, Linda
dc.contributor.authorScott, E. Marian
dc.contributor.authorCocchi, Daniela
dc.contributor.authorIllian, Janine B.
dc.date.accessioned2016-06-04T23:32:33Z
dc.date.available2016-06-04T23:32:33Z
dc.date.issued2015
dc.identifier.citationAltieri , L , Scott , E M , Cocchi , D & Illian , J B 2015 , ' A changepoint analysis of spatio-temporal point processes ' , Spatial Statistics . https://doi.org/10.1016/j.spasta.2015.05.005en
dc.identifier.issn2211-6753
dc.identifier.otherPURE: 193833318
dc.identifier.otherPURE UUID: 7feb0d44-91a7-4288-af21-2d6b86800a03
dc.identifier.otherRIS: urn:099D61B8750E7EDC20D30E349A17C092
dc.identifier.otherScopus: 84933575779
dc.identifier.otherWOS: 000368913100007
dc.identifier.urihttp://hdl.handle.net/10023/8935
dc.descriptionAs regards author Linda Altieri, the research work underlying this paper was partially funded by a FIRB 2012 grant (project no. RBFR12URQJ; title: Statistical modeling of environmental phenomena: pollution, meteorology, health and their interactions) for research projects by the Italian Ministry of Education, Universities and Research.en
dc.description.abstractThis work introduces a Bayesian approach to detecting multiple unknown changepoints over time in the inhomogeneous intensity of a spatio-temporal point process with spatial and temporal dependence within segments. We propose a new method for detecting changes by fitting a spatio-temporal log-Gaussian Cox process model using the computational efficiency and flexibility of integrated nested Laplace approximation, and by studying the posterior distribution of the potential changepoint positions. In this paper, the context of the problem and the research questions are introduced, then the methodology is presented and discussed in detail. A simulation study assesses the validity and properties of the proposed methods. Lastly, questions are addressed concerning potential unknown changepoints in the intensity of radioactive particles found on Sandside beach, Dounreay, Scotland.
dc.language.isoeng
dc.relation.ispartofSpatial Statisticsen
dc.rights© 2015, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (http://creativecommons.org/licenses/by-nc-nd/4.0/)en
dc.subjectSpatio-temporal point processesen
dc.subjectChangepoint analysisen
dc.subjectINLAen
dc.subjectRadioactive particle dataen
dc.subjectQA Mathematicsen
dc.subjectNDASen
dc.subject.lccQAen
dc.titleA changepoint analysis of spatio-temporal point processesen
dc.typeJournal articleen
dc.description.versionPostprinten
dc.contributor.institutionUniversity of St Andrews.School of Mathematics and Statisticsen
dc.contributor.institutionUniversity of St Andrews.Scottish Oceans Instituteen
dc.contributor.institutionUniversity of St Andrews.Centre for Research into Ecological & Environmental Modellingen
dc.identifier.doihttps://doi.org/10.1016/j.spasta.2015.05.005
dc.description.statusPeer revieweden
dc.date.embargoedUntil2016-06-05


This item appears in the following Collection(s)

Show simple item record