title: Robust discriminant analysis and its application to identify protein coding regions of rice genes.
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.
authors.affiliation: Department of Statistics and Financial Mathematics, School of Mathematical Sciences, Beijing Normal University, Ministry of Education, Beijing, China.
authors.forename: Jiao
authors.initials: J
authors.lastname: Jin
authors.forename: Jinbing
authors.initials: J
authors.lastname: An
mesh_terms: D016002:Discriminant Analysis; D018745:Genome, Plant; D016366:Open Reading Frames; D012275:Oryza / Q000235:genetics*; D010940:Plant Proteins / Q000235:genetics*
chemical_list: D010940:Plant Proteins