DISCRIMINANT ANALYSIS BASED ON STATISTICAL DEPTH

Jiao JIN;Hengjian CUI

Journal of Systems Science & Complexity ›› 2010, Vol. 23 ›› Issue (2) : 362-371.

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中国科学院数学与系统科学研究院期刊网
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Journal of Systems Science & Complexity ›› 2010, Vol. 23 ›› Issue (2) : 362-371. DOI: 10.1007/s11424-010-7214-x
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DISCRIMINANT ANALYSIS BASED ON STATISTICAL DEPTH

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Abstract

In the past two decades, many statistical depth functions seemed as powerful exploratory and inferential tools for multivariate data analysis have been presented. In this paper, a new depth function family that meets four properties mentioned in Zuo and Serfling (2000) is proposed. Then a classification rule based on the depth function family is proposed. The classification parameter b could be modified according to the type-I error α, and the estimator of b has the consistency and achieves the convergence rate n−1/2. With the help of the proper selection for depth family parameter c, the approach for discriminant
analysis could minimize the type-II error β. A simulation study and a real data example compare the performance of the different discriminant methods.

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Depth / discriminant analysis / location parameter / MVE / scatter matrix.

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Jiao JIN , Hengjian CUI. DISCRIMINANT ANALYSIS BASED ON STATISTICAL DEPTH. Journal of Systems Science and Complexity, 2010, 23(2): 362-371 https://doi.org/10.1007/s11424-010-7214-x
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