Asymptotically uniformly most powerful tests in parametric and semiparametric models
type: Item
instance of: scholarly article
title: Asymptotically uniformly most powerful tests in parametric and semiparametric models
zbMATH Open document ID: 0860.62020
author: Sungsub Choi
author: W. J. Hall
author: Anton Schick
published in: The Annals of Statistics
publication date: 1997-04-16T00:00:00Z
Mathematics Subject Classification ID: 62F05
Mathematics Subject Classification ID: 62G10
Mathematics Subject Classification ID: 62G20
Mathematics Subject Classification ID: 62A01
zbMATH DE Number: 950556
zbMATH Keywords: local alternatives
zbMATH Keywords: effective scores
zbMATH Keywords: efficient tests
zbMATH Keywords: adaptation
zbMATH Keywords: asymptotically uniformly most powerful tests
zbMATH Keywords: semiparametric model
zbMATH Keywords: moving alternative
zbMATH Keywords: local asymptotic normality
zbMATH Keywords: unbiased tests
zbMATH Keywords: asymptotic invariance principle
zbMATH Keywords: multidimensional hypotheses
zbMATH Keywords: invariant tests
zbMATH Keywords: likelihood ratio tests
zbMATH Keywords: Neyman-Rao tests
zbMATH Keywords: asymptotically uniformly most accurate confidence sets
zbMATH Keywords: linear regression model
zbMATH Keywords: proportional hazards regression model
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1214/aos/1032894469
OpenAlex ID: W2060277929
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DOI: 10.1214/AOS/1032894469
description: scientific article; zbMATH DE number 950556