Sharp optimality for regression with real-time data

被引：0

作者：

Luo, Zhi-Ming ^{[1
]}

Ha, Jeongcheol ^{[1
]}

Kim, Tae Yoon ^{[1
]}

Park, Inho ^{[2
]}

机构：

[1] Keimyung Univ, Dept Stat, Daegu 704701, South Korea

[2] Pukyong Natl Univ, Dept Stat, Busan 608737, South Korea

来源：

JOURNAL OF THE KOREAN STATISTICAL SOCIETY | 2015年 / 44卷 / 04期

基金：

新加坡国家研究基金会;

关键词：

Minimax; Optimal rate of convergence; Exact constant of convergence; Real-time data; SUP-NORM LOSS; NONPARAMETRIC REGRESSION; CONVERGENCE; CONSTANT; RATES;

D O I：

10.1016/j.jkss.2015.04.004

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

A minimax estimator for a nonparametric regression model is proposed when real-time data are assumed and its asymptotic behavior of minimax risk in the sup-norm for the Holder function class is studied. The optimal rate of convergence and exact minimax constant are found for the estimator. (C) 2015 The Korean Statistical Society. Published by Elsevier B.V. All rights reserved.

引用

页码：632 / 645

页数：14

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