Boral- Bayesian Ordination and Regression Analysis of Multivariate Abundance Data in R

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dc.contributor.authorHui, Francis K.C.
dc.date.accessioned2016-08-18T05:51:25Z
dc.date.available2016-08-18T05:51:25Z
dc.date.issued2016
dc.description.abstractModel-based methods have emerged as a powerful approach for analysing multivariate abundance data in community ecology. Key applications include model-based ordination, modelling the various sources of correlations across species, and making inferences while accounting for these between species correlations. boral (version 0.9.1, licence GPL-2) is an r package available on cran for model-based analysis of multivariate abundance data, with estimation performed using Bayesian Markov chain Monte Carlo methods. A key feature of the boral package is the ability to incorporate latent variables as a parsimonious method of modelling between species correlation. Pure latent variable models offer a model-based approach to unconstrained ordination, for visualizing sites and the indicator species characterizing them on a low-dimensional plot. Correlated response models consist of fitting generalized linear models to each species, while including latent variables to account for residual correlation between species, for example, due to unmeasured covariates.en_AU
dc.description.sponsorshipThis research was supported by the Australian Research Council discovery project grant DP140101259.en_AU
dc.identifier.issn2041-210Xen_AU
dc.identifier.urihttp://hdl.handle.net/1885/107231
dc.publisherWileyen_AU
dc.relationhttp://purl.org/au-research/grants/arc/DP140101259en_AU
dc.rights© 2015 The Author. Methods in Ecology and Evolution © 2015 British Ecological Societyen_AU
dc.sourceMethods in Ecology and Evolutionen_AU
dc.subjectBayesian inferenceen_AU
dc.subjectcommunity compositionen_AU
dc.subjectgeneralized linear modelsen_AU
dc.subjecthierarchicalmodelsen_AU
dc.subjectlatent variable modelen_AU
dc.subjectspecies interactionen_AU
dc.titleBoral- Bayesian Ordination and Regression Analysis of Multivariate Abundance Data in Ren_AU
dc.typeJournal articleen_AU
local.bibliographicCitation.issue6en_AU
local.bibliographicCitation.lastpage750en_AU
local.bibliographicCitation.startpage744en_AU
local.contributor.affiliationHui, F. K. C.,en_AU
local.contributor.authoremailfhui28@gmail.comen_AU
local.contributor.authoruidu1001205en_AU
local.identifier.citationvolume7en_AU
local.identifier.doi10.1111/2041-210X.12514en_AU
local.identifier.uidSubmittedByu1005913en_AU
local.publisher.urlhttp://au.wiley.com/WileyCDA/en_AU
local.type.statusPublished Versionen_AU

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