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Robust discriminant analysis and its application to identify protein coding regions of rice genes
Authors:Jin Jiao  An Jinbing
Affiliation:a Department of Statistics and Financial Mathematics, School of Mathematical Sciences, Beijing Normal University, Laboratory of Mathematics and Complex Systems (Beijing Normal University), Ministry of Education, Beijing 100875, China
b Faculty of Foundation Education, Peking University Health Science Center, Beijing 100083, China
Abstract:Identification of protein coding regions is fundamentally a statistical pattern recognition problem. Discriminant analysis is a statistical technique for classifying a set of observations into predefined classes and it is useful to solve such problems. It is well known that outliers are present in virtually every data set in any application domain, and classical discriminant analysis methods (including linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA)) do not work well if the data set has outliers. In order to overcome the difficulty, the robust statistical method is used in this paper. We choose four different coding characters as discriminant variables and an approving result is presented by the method of robust discriminant analysis.
Keywords:Robust discriminant analysis   Identification   Protein coding regions   Rice genes
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