The Strong Consistency of the Conditional Probability of Error in Discrimination Based on Kernel Stereographic Projection Density Estimator

摘要：

Let (X,Y), (X_1,Y_1),…,(X_n,Y_m) be R~d×1,…,M -valued i.i.d. random vectors, Z_n=(X_1,Y_1),…(X_n,Y_ri).(X,Y) is distribution free, to discriminate Y based on Z_n and X belongs to nonparametric discrimination. Based on kernel stereographic projection density estimator (KSPDE), a new nonparametric discriminate rule is constructed. Under some weak conditions(see theorem 1), the exponential convergence rate and the strong consistency of the conditional probability of error in discrimination are obtained.

关键词： stereographic projection transformation kernel density estimator nonparametric discrimination the conditional probability of error in discrimination

作者: SU Yan YANG Zhenhai

作者单位: School of Mathematics and Physics, North China Electric Power University, Baoding, P.R.China,071003 College of Applied Science, Beijing University of Technology, Beijing, P.R.China, 100124

会议类型: 国际会议

会议名称: The 3rd International Institute of Statistics & Management Engineering Symposium(2010 国际统计与管理工程研讨会 IISMES)

会议地点: 威海

会议语种:英文

页码: 508-511

在线出版日期: 2010-07-24（万方平台首次上网日期，不代表论文的发表时间）