Using empirical partially Bayes inference for increased efficiency
type: Item
instance of: scholarly article
title: Using empirical partially Bayes inference for increased efficiency
zbMATH Open document ID: 0601.62044
published in: The Annals of Statistics
publication date: 1985-01-01T00:00:00Z
review text: The author shows how empirical partially Bayes methods can be utilized as a means for improving the efficiency of an estimator of the structural parameter in a class of problems in which the number of nuisance parameters increases to infinity. It is proposed to estimate the structural parameter in an asymptotically unbiased way and apply James- Stein shrinkage to the nuisance parameter estimators. It is shown that when the shrinkage estimators are carefully chosen, this yields estimators generally more efficient than the maximum likelihood one.
Mathematics Subject Classification ID: 62F12
Mathematics Subject Classification ID: 62F10
Mathematics Subject Classification ID: 62F15
zbMATH DE Number: 3969882
zbMATH Keywords: James-Stein effect
zbMATH Keywords: score function
zbMATH Keywords: James-Stein estimators
zbMATH Keywords: consistency
zbMATH Keywords: empirical partially Bayes methods
zbMATH Keywords: efficiency
zbMATH Keywords: structural parameter
zbMATH Keywords: nuisance parameters
zbMATH Keywords: asymptotically unbiased
zbMATH Keywords: James-Stein shrinkage
zbMATH Keywords: maximum likelihood
author: Bruce G. Lindsay
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1214/aos/1176349646
OpenAlex ID: W1968176681
DOI: 10.1214/AOS/1176349646
description: scientific article; zbMATH DE number 3969882