On the convergence rates of empirical Bayes rules for two-action problems: Discrete case
type: Item
instance of: scholarly article
title: On the convergence rates of empirical Bayes rules for two-action problems: Discrete case
zbMATH Open document ID: 0653.62007
published in: The Annals of Statistics
publication date: 1988-01-01T00:00:00Z
review text: The purpose of this paper is to investigate the convergence rates of a sequence of empirical Bayes decision rules for the two-action decision problems where the distributions of the observations belong to a discrete exponential family. It is found that the sequence of the empirical Bayes decision rules under study is asymptotically optimal, and the order of associated convergence rates is O(exp(-cn)), for some positive constant c, where n is the number of accumulated past experience (observations) at hand. Two examples are provided to illustrate the performance of the proposed empirical Bayes decision rules. A comparison is also made between the proposed empirical Bayes rules and some earlier existing empirical Bayes rules.
Mathematics Subject Classification ID: 62C12
Mathematics Subject Classification ID: 62C10
zbMATH DE Number: 4066124
zbMATH Keywords: convergence rates
zbMATH Keywords: sequence of empirical Bayes decision rules
zbMATH Keywords: two-action decision problems
zbMATH Keywords: discrete exponential family
zbMATH Keywords: asymptotically optimal
zbMATH Keywords: Bayes rules
author: Tachen Liang
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1214/aos/1176351058
OpenAlex ID: W1965671629
DOI: 10.1214/AOS/1176351058
description: scientific article; zbMATH DE number 4066124