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Universitat de Girona. Departament d’Informà tica i Matemà tica Aplicada | |
Ulbrich, H.F. | |
Visualization of data becomes more challenging as the dimensionality of the data increases,impacting not only the display of the data itself but also the modeling results.This paper discusses common visualization techniques for compositional data. None of themseem to be well suited for changes in compositions that depend on either a metric covariate or afactor. The clr-deviation chart as a chart with a factor or covariate as abscissa and all centered logratio-transformed component values superimposed on the ordinate axis is then introduced jointlywith the clr-component chart. The clr-deviation chart takes advantage of the sum-equals-zeroproperty of clr-transformed compositional data. It has some theoretical and practical advantagesover alternatives and one major disadvantage – an arbitrarily scaled ordinate axis; its propertiesare discussed.The usefulness of the methods are illustrated using an example analyzing the changes of proportionsof the different diseases treated by hospitalization over a period of 13 years in Germany | |
http://hdl.handle.net/2072/273425 | |
eng | |
Universitat de Girona. Departament d’Informà tica i Matemà tica Aplicada | |
Tots els drets reservats | |
Anà lisi multivariable -- Congressos
Multivariate analysis -- Congresses EstadÃstica matemà tica -- Congressos Mathematical statistics -- Congresses |
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Graphing and Communicating Compositional Data in High Dimensions | |
info:eu-repo/semantics/conferenceObject | |
Recercat |