VDA (version 1.01)

VDA: Multicategory Vertex Discriminant Analysis

Description

This package provides functions to optimize and execute Multicategory Vertex Discriminant Analysis, a method of supervised learning for an outcome with k predictor categories. Outcome classification is based on linear discrimination among the vertices of a regular simplex in a k-1-dimension Euclidean space, where each vertex represents a different category.

Details

ll{ Package: VDA Type: Package Version: 1.0 Date: 2012-02-27 License: GPL-2 LazyLoad: yes }

References

Lange, K. and Wu, T.T. (2008) An MM Algorithm for Multicategory Vertex Discriminant Analysis. Journal of Computational and Graphical Statistics, Volume 17, No 3, 527-544.

Examples

#load dataset from package
data(zoo)

#matrix containing all predictor vectors
x <- zoo[,2:17]

#outcome class vector
y <- zoo[,18]

#run VDA
out <- VDA_R(x, y)