基于NOD误差的非参数回归模型估计的渐近性质

展开
  • School of Mathematical Sciences, Anhui University
PENG Zhi-qing(1989-), male, native of Anqing, Anhui, M.S.D., engages in probability limit theorem; WANG Xue-jun(1981-), male, native of Hefei, Anhui, an associate professor of Anhui Universiry, Ph.D., engages in probability limit theorem.

收稿日期: 2013-12-21

  网络出版日期: 2020-11-24

基金资助

Supported by the Research Teaching Model Curriculum of Anhui University(xjyjkc1407); Supported by the Students Innovative Training Project of Anhui University(201310357004,201410357117,201410357249); Supported by the Quality Improvement Projects for Undergraduate Education of Anhui University(ZLTS2015035);

Asymptotic Property for the Estimator of Nonparametric Regression Models Under Negatively Orthant Dependent Errors

Expand
  • School of Mathematical Sciences, Anhui University
PENG Zhi-qing(1989-), male, native of Anqing, Anhui, M.S.D., engages in probability limit theorem; WANG Xue-jun(1981-), male, native of Hefei, Anhui, an associate professor of Anhui Universiry, Ph.D., engages in probability limit theorem.

Received date: 2013-12-21

  Online published: 2020-11-24

Supported by

Supported by the Research Teaching Model Curriculum of Anhui University(xjyjkc1407); Supported by the Students Innovative Training Project of Anhui University(201310357004,201410357117,201410357249); Supported by the Quality Improvement Projects for Undergraduate Education of Anhui University(ZLTS2015035);

摘要

In this paper, by using some inequalities of negatively orthant dependent(NOD,in short) random variables and the truncated method of random variables, we investigate the nonparametric regression model. The complete consistency result for the estimator of g(x) is presented. 

本文引用格式

彭智庆, 郑璐璐, 刘艳芳, 潇如, 王学军 . 基于NOD误差的非参数回归模型估计的渐近性质[J]. 数学季刊, 2015 , 30(2) : 300 -307 . DOI: 10.13371/j.cnki.chin.q.j.m.2015.02.018

Abstract

In this paper, by using some inequalities of negatively orthant dependent(NOD,in short) random variables and the truncated method of random variables, we investigate the nonparametric regression model. The complete consistency result for the estimator of g(x) is presented. 
文章导航

/