Asymptotic minimax estimation in semiparametric models
type: Item
instance of: scholarly article
title: Asymptotic minimax estimation in semiparametric models
zbMATH Open document ID: 0734.62031
DOI: 10.1007/BF01193584
publication date: 1991-01-01T00:00:00Z
review text: The author considers the problem of efficient and minimax estimation of score functions and the parametric components in semiparametric models. Sufficient conditions are given under which the estimator is asymptotically efficient, i.e., it has asymptotic normal distribution with minimum variance. The estimator is also shown to be asymptotically minimax under convex loss functions. A few examples are discussed.
Mathematics Subject Classification ID: 62F12
Mathematics Subject Classification ID: 62C20
zbMATH DE Number: 4215165
zbMATH Keywords: nuisance parameter
zbMATH Keywords: minimax estimation of score functions
zbMATH Keywords: parametric components
zbMATH Keywords: semiparametric models
zbMATH Keywords: asymptotic normal distribution
zbMATH Keywords: minimum variance
zbMATH Keywords: asymptotically minimax
zbMATH Keywords: convex loss
author: Byeong U. Park
reviewed by: Rasul A. Khan
MaRDI profile type: Publication
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full work available at URL: https://doi.org/10.1007/bf01193584
OpenAlex ID: W2030628403
published in: Zeitschrift für Wahrscheinlichkeitstheorie und Verwandte Gebiete
description: scientific article; zbMATH DE number 4215165