Biplots

Abstract

Biplots are a multivariate scatterplot concept to visualize row and column structures in complex data. It can be applied to any of the exploratory methods presented in previous chapters. We introduce biplots by means of a multivariate regression with two predictors. Subsequently, this concept is applied to principal component analysis, where biplots are one of the classical output visualization techniques. The same plotting principle is adopted to Princals. In the following section, biplots for multidimensional scaling are introduced where external covariates are mapped onto the configuration. Finally, biplots within a correspondence analysis context are discussed where they are simply asymmetric maps.