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 α-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.
Citation
Niël J. le Roux. Sugnet Gardner. "Analysing Your Multivariate Data as a Pictorial: A Case for Applying Biplot Methodology?." Internat. Statist. Rev. 73 (3) 365 - 387, December 2005.
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