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• W2153993385 abstract "This paper illustrates the versatility of biplot methodology when analysing multivariate data from diverse disciplines. The modern approach of Gower & Hand (1996) whereby biplots are regarded as multivariate analogues of ordinary scatter plots is utilised for extending biplot methodology introducing several novel applications. Focus is on biplot applications where the merits of principal component biplots and canonical variate analysis biplots are illustrated with data sets from higher education, the manufacturing industry, the mining industry, agriculture, finance and archaeology. It is shown how to equip biplots with quality regions, classification regions and acceptance regions; how a-bags superimposed on biplots provide a quantification of the multidimensional overlap of classes as well as enable biplots to be used with large data sets; how to use biplots for exploring multi-dimensional reality and in sophisticated classification procedures. Cet article illustre la souplesse de la méthodologie biplot vis-à-vis de l'analyse des données à plusieurs variables dans diverses disciplines. On utilise l'approche moderne de Gower & Hand (1996), où les biplots sont considérés comme des équivalents à plusieurs variables des graphes diffus ordinaires, pour étendre la méthodologie biplot en introduisant plusieurs applications originales. L'accent est mis sur les applications où les avantages des biplots àéléments principaux et des biplots issus d'analyse à variables canoniques sont illustrés sur des ensembles de données issus de l'éducation supérieure, des entreprises industrielles, de l'industrie minière, de l'agriculture, de la finance et de l'archéologie. On montre comment munir les biplots de domaines de qualité, de classification et d'acceptance; comment des alpha-sacs ajoutés aux biplots procurent une quantification de la superposition multidimensionnelle des classes en même temps qu'ils permettent d'utiliser les biplots avec des grands ensembles de données; et comment utiliser les biplots dans l'étude de détail de la réalité multidimensionnelle et dans des processus de classification compliqués." @default.
• W2153993385 created "2016-06-24" @default.
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• W2153993385 date "2006-12-14" @default.
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• W2153993385 title "Analysing Your Multivariate Data as a Pictorial: A Case for Applying Biplot Methodology?" @default.
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• W2153993385 doi "https://doi.org/10.1111/j.1751-5823.2005.tb00154.x" @default.
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