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dc.contributor.authorBorchers, David Louis
dc.contributor.authorKidney, Darren
dc.date.accessioned2016-07-15T12:30:16Z
dc.date.available2016-07-15T12:30:16Z
dc.date.issued2014-07-01
dc.identifier.citationBorchers , D L & Kidney , D 2014 , Flexible density surface estimation for spatially explicit capture-recapture surveys . CREEM TEchnical Report , no. 2014-1 , University of St Andrews .en
dc.identifier.otherPURE: 244334181
dc.identifier.otherPURE UUID: c426b438-898b-479d-8ccb-976c71e0bd5d
dc.identifier.otherORCID: /0000-0002-3944-0754/work/72842435
dc.identifier.urihttp://hdl.handle.net/10023/9147
dc.description.abstract1. Existing spatially explicit capture-recapture (SECR) software does not have the ability to fit flexible nonparametric models of animal density. 2. We describe and implement in the R package secrgam, a flexible method for estimating density surfaces from SECR data, using regression splines. 3. Package secrgam is an extension of package secr to implement some models available in the generalised additive model package mvcv. It accommodates density models that are arbitrarily flexible functions of spatially- and temporally-referenced variables. This includes one-dimensional and multi-dimensional smooths of covariates and smooths with interactions. The shape and smoothness of the fitted density surfaces is data-driven and can be determined using AIC or similar criteria. We illustrate use of the package by estimating the density surface from a simulated camera trap survey of leopards. 4. Package secrgam provides a flexible tool for species distribution modelling using SECR data.
dc.format.extent16
dc.language.isoeng
dc.publisherUniversity of St Andrews
dc.relation.ispartofseriesCREEM TEchnical Reporten
dc.subjectSpatially explicit capture-recaptureen
dc.subjectGeneralised additive modelen
dc.subjectSpecies distribution modelen
dc.subjectDensity estimationen
dc.subjectQA Mathematicsen
dc.subjectQH301 Biologyen
dc.subject.lccQAen
dc.subject.lccQH301en
dc.titleFlexible density surface estimation for spatially explicit capture-recapture surveysen
dc.typeReporten
dc.description.versionPostprinten
dc.contributor.institutionUniversity of St Andrews.School of Mathematics and Statisticsen
dc.contributor.institutionUniversity of St Andrews.Marine Alliance for Science & Technology Scotlanden
dc.contributor.institutionUniversity of St Andrews.Scottish Oceans Instituteen
dc.contributor.institutionUniversity of St Andrews.Centre for Research into Ecological & Environmental Modellingen


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