The Analysis of binary data in quantitative plant ecology

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dc.contributor.advisor Mitchell, Neil en
dc.contributor.advisor Wild, Chris en Yee, Thomas William en 2007-10-26T01:27:23Z en 2007-10-26T01:27:23Z en 1993 en
dc.identifier.citation Thesis (PhD--Mathematics and Statistics, and Botany)--University of Auckland, 1993. en
dc.identifier.uri en
dc.description Whole document restricted, but available by request, use the feedback form to request access. en
dc.description.abstract The analysis of presence/absence data of plant species by regression analysis is the subject of this thesis. A nonparametric approach is emphasized, and methods which take into account correlations between species are also considered. In particular, generalized additive models (GAMs) are used, and these are applied to species’ responses to greenhouse scenarios and to examine multispecies interactions. Parametric models are used to estimate optimal conditions for the presence of species and to test several niche theory hypotheses. An extension of GAMs called vector GAMs is proposed, and they provide a means for proposing nonparametric versions of the following models: multivariate regression, the proportional and nonproportional odds model, the multiple logistic regression model, and bivariate binary regression models such as bivariate probit model and the bivariate logistic model. Some theoretical properties of vector GAMs are deduced from those pertaining to ordinary GAMs, and its relationship with the generalized estimating equations (GEE) approach elucidated. en
dc.format Scanned from print thesis en
dc.language.iso en en
dc.publisher ResearchSpace@Auckland en
dc.relation.ispartof PhD Thesis - University of Auckland en
dc.relation.isreferencedby UoA519384 en
dc.rights Whole document restricted but available by request. Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. en
dc.rights.uri en
dc.title The Analysis of binary data in quantitative plant ecology en
dc.type Thesis en Mathematics, Statistics and Botany en The University of Auckland en Doctoral en PhD en
dc.subject.marsden Fields of Research::230000 Mathematical Sciences::230200 Statistics en
dc.subject.marsden Fields of Research::270000 Biological Sciences::270400 Botany en
dc.rights.holder Copyright: The author en
pubs.local.anzsrc 01 - Mathematical Sciences en Faculty of Science en

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