Sample size and class variability in the choice of a method of discriminant analysis

Abstract

The choice between linear and quadratic discriminant analysis in a simulation, (where DN values are normally distributed within classes and the classes are of known prior probability), is shown to depend on the size of the training sample and the extent to which the within-class variance-covariance matrices difTer from each other.