Correspondence analysis of raw data

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Ecology, 2010, 91(4), pp. 958-963
http://hdl.handle.net/10230/494
To cite or link this document: http://hdl.handle.net/10230/494
dc.contributor.author Greenacre, Michael
dc.contributor.other Universitat Pompeu Fabra. Departament d'Economia i Empresa
dc.date.issued 2008-09-01
dc.identifier.citation Ecology, 2010, 91(4), pp. 958-963
dc.identifier.uri http://hdl.handle.net/10230/494
dc.description.abstract Correspondence analysis has found extensive use in ecology, archeology, linguistics and the social sciences as a method for visualizing the patterns of association in a table of frequencies or nonnegative ratio-scale data. Inherent to the method is the expression of the data in each row or each column relative to their respective totals, and it is these sets of relative values (called profiles) that are visualized. This ‘relativization’ of the data makes perfect sense when the margins of the table represent samples from sub-populations of inherently different sizes. But in some ecological applications sampling is performed on equal areas or equal volumes so that the absolute levels of the observed occurrences may be of relevance, in which case relativization may not be required. In this paper we define the correspondence analysis of the raw ‘unrelativized’ data and discuss its properties, comparing this new method to regular correspondence analysis and to a related variant of non-symmetric correspondence analysis.
dc.language.iso eng
dc.relation.ispartofseries Economics and Business Working Papers Series; 1112
dc.rights L'accés als continguts d'aquest document queda condicionat a l'acceptació de les condicions d'ús establertes per la següent llicència Creative Commons
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.title Correspondence analysis of raw data
dc.type info:eu-repo/semantics/workingPaper
dc.date.modified 2014-06-03T07:14:23Z
dc.subject.keyword Statistics, Econometrics and Quantitative Methods
dc.subject.keyword abundance data
dc.subject.keyword biplot
dc.subject.keyword bray-curtis dissimilarity
dc.subject.keyword profile
dc.subject.keyword size and shape
dc.subject.keyword visualisation
dc.rights.accessRights info:eu-repo/semantics/openAccess


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