Quadratic Discriminant Analysis for High-Dimensional Data

  title={Quadratic Discriminant Analysis for High-Dimensional Data},
  author={Yilei Wu and Yingli Qin and Mu Zhu},
  journal={Statistica Sinica},
High-dimensional classification is an important and challenging statistical problem. We develop a set of quadratic discriminant rules by simplifying the structure of the covariance matrices instead of imposing sparsity assumptions — either on the covariance matrices themselves (or their inverses), or on the standardized between-class distance. Under moderate conditions on the population covariance matrices, our specialized quadratic discriminant rules enjoy good asymptotic properties… 

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