ROBUST ESTIMATION USING THE ROBBINS-MONRO STOCHASTIC-APPROXIMATION ALGORITHM

被引：8

作者：

PRICE, EL ^{[1
]}

VANDELINDE, VD ^{[1
]}

机构：

[1] JOHNS HOPKINS UNIV,DEPT ELECT ENGN,BALTIMORE,MD 21218

来源：

IEEE TRANSACTIONS ON INFORMATION THEORY | 1979年 / 25卷 / 06期

关键词：

D O I：

10.1109/TIT.1979.1056111

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The problem of minmax estimation of a location parameter Introduced by Huber is considered. It is shown that under general conditions there exists a solution which is a form of the Robbins–Monro stochastic approximation algorithm. This generalizes earlier work by Martin and Masreliez who have given stochastic approximation (SA)-estimate solutions for two particular cases. As with the M-estimate solutions given by Huber, the SA solutions are completely determined by the probability distribution function with least Fisher information in the distribution set used to model the observation errors. ©1979 IEEE

引用

页码：698 / 704

页数：7

共 15 条

[1]

Ash R. B., 2014, REAL ANAL PROBABILIT

[2] 1972 WALD LECTURE - ROBUST STATISTICS - REVIEW [J].