An Extended Projection Data Depth and Its Applications to Discrimination |
| |
Authors: | Xia Cui Lu Lin Guangren Yang |
| |
Institution: | 1. School of Mathematics , Shandong University , Jinan, Shandong Province, P.R. China xcui@ mail.sdu.edu.cn;3. School of Mathematics , Shandong University , Jinan, Shandong Province, P.R. China;4. Department of Statistics , Jinan University , Guangzhou, Guandong Province, P.R. China |
| |
Abstract: | This article investigates the possible use of our newly defined extended projection depth (abbreviated to EPD) in nonparametric discriminant analysis. We propose a robust nonparametric classifier, which relies on the intuitively simple notion of EPD. The EPD-based classifier assigns an observation to the population with respect to which it has the maximum EPD. Asymptotic properties of misclassification rates and robust properties of EPD-based classifier are discussed. A few simulated data sets are used to compare the performance of EPD-based classifier with Fisher's linear discriminant rule, quadratic discriminant rule, and PD-based classifier. It is also found that when the underlying distributions are elliptically symmetric, EPD-based classifier is asymptotically equivalent to the optimal Bayes classifier. |
| |
Keywords: | Bayes risk Breakdown points Discriminant analysis Misclassi-fication rate Projection data depth |
|
|