MultBiplotR: A package for Multivariate Analysis using Biplots
Ponente: José Luis Vicente Villardón
Descripción: Biplot methods allow for the simultaneous graphical representations of the rows and columns of a data matrix.; that is useful to visually explore patterns arising from data and also to visually interpret the results more formal statistical models.
Classical and most popular biplot methods are closely related to Principal Components Analysis although the methodology can be extended to any kind of data or many other multivariate techniques.
MultBiplotR includes biplot representations associated to different multivariate techniques as Discriminant Analysis, Canonical Analysis, One and Two Way MANOVA; Simple, Multiple and Canonical Correspondence Analysis, Factor Analysis, Statis-ACT, X-Statis, DISTATIS, Common Principal Components,  CoInertia, Redundancy Analysis, Consensus PCA with different consensus criteria, Item response theory models, Unfolding, Constrained Unfolding, vector models on any Euclidean configuration resulting from Principal Coordinates or Multidimensional Scaling methods, Partial Least Squares, etc.
It also includes recently developed biplot representations for categorical data, Logistic Biplots for Binary, Nominal and Ordinal Data.
The package is an R implementation of the MultBiplot package developed in Matlab and used in many scientific papers.  (
Many of the representations have been developed at the Department of Statistics, by the research group RGBIPLOT of the University of Salamanca.
The package will include the future developments of the research group.