Contribution biplots

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Greenacre, Michael. Contribution biplots. 2009
http://hdl.handle.net/10230/5600
To cite or link this document: http://hdl.handle.net/10230/5600
dc.contributor.author Greenacre, Michael
dc.contributor.other Universitat Pompeu Fabra. Departament d'Economia i Empresa
dc.date.issued 2009-07-01
dc.identifier.uri http://hdl.handle.net/10230/5600
dc.description.abstract In order to interpret the biplot it is necessary to know which points – usually variables – are the ones that are important contributors to the solution, and this information is available separately as part of the biplot’s numerical results. We propose a new scaling of the display, called the contribution biplot, which incorporates this diagnostic directly into the graphical display, showing visually the important contributors and thus facilitating the biplot interpretation and often simplifying the graphical representation considerably. The contribution biplot can be applied to a wide variety of analyses such as correspondence analysis, principal component analysis, log-ratio analysis and the graphical results of a discriminant analysis/MANOVA, in fact to any method based on the singular-value decomposition. In the contribution biplot one set of points, usually the rows of the data matrix, optimally represent the spatial positions of the cases or sample units, according to some distance measure that usually incorporates some form of standardization unless all data are comparable in scale. The other set of points, usually the columns, is represented by vectors that are related to their contributions to the low-dimensional solution. A fringe benefit is that usually only one common scale for row and column points is needed on the principal axes, thus avoiding the problem of enlarging or contracting the scale of one set of points to make the biplot legible. Furthermore, this version of the biplot also solves the problem in correspondence analysis of low-frequency categories that are located on the periphery of the map, giving the false impression that they are important, when they are in fact contributing minimally to the solution.
dc.language.iso eng
dc.relation.ispartofseries Economics and Business Working Papers Series; 1162
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 Contribution biplots
dc.type info:eu-repo/semantics/workingPaper
dc.date.modified 2014-06-03T07:14:24Z
dc.subject.keyword Statistics, Econometrics and Quantitative Methods
dc.subject.keyword biplot
dc.subject.keyword contributions
dc.subject.keyword correspondence analysis
dc.subject.keyword discriminant analysis
dc.subject.keyword log-ratio analysis
dc.subject.keyword manova
dc.subject.keyword principal component analysis
dc.subject.keyword scaling
dc.subject.keyword singular value decomposition
dc.subject.keyword weighting.
dc.rights.accessRights info:eu-repo/semantics/openAccess


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