The Convergence Rate with Bootstrap for Multidimensional Density Functional Kernel Estimation

摘要：

　　Bootstrap method is a statistical method proposed by the American Stanford University professor of Statistics Efron,which belongs to the parameters of statistical methods.According to a given sub-sample,we do not need its distributional assumptions or increase the sample information which can be described the overall distribution characteristics of statistical inference.The basic idea of the Bootstrap statistics is unknown and can not repeat the sampling distribution function instead of using a repeat sampling of the distribution function estimates.The independent identically distributed random variable series x1,…,xn,have the common probability density function,with μ =Ex1.In the paper,combining with multidimensional density function,we discuss the convergence rate with Bootstrap method for the kemel estimation fm((x)) of the density functional θ =f (μ).

关键词： Bootstrap Density Functional Kernel Estimation Convergence Rate

作者: Dewang Li

作者单位: Department of Mathematics,Hechi University,Yizhou Guangxi 546300,China.

会议类型: 国际会议

会议名称: the 2012 International Conference on Manufacturing Engineering and Automation (2012年制造工程与自动化国际会议(ICMEA2012))

会议地点: 广州

会议语种:英文

页码: 2559-2563

在线出版日期: 2012-11-16（万方平台首次上网日期，不代表论文的发表时间）