On BIC's Selection Consistency for Discriminant Analysis
15 Pages Posted: 24 Nov 2008 Last revised: 13 Oct 2009
Date Written: October 21, 2008
Abstract
Linear and/or quadratic discriminant analysis (based on finite Gaussian mixture) is one of the most useful classification methods, for which the problem of variable selection is poorly understood. To fill this important theoretical gap, a novel BIC-type selection criterion in conjunction with a backward elimination procedure is proposed. We show theoretically that the new method is able to identify the true Gaussian structure consistently, even with a heteroscedastic covariance structure. Numerical studies are presented to demonstrate the new method's usefulness.
Keywords: BIC, Discriminant Analysis, Gaussian Mixture
JEL Classification: C52, C14
Suggested Citation: Suggested Citation
