Hypothesis testing with a restricted parameter space
type: Item
instance of: scholarly article
title: Hypothesis testing with a restricted parameter space
zbMATH Open document ID: 0947.62014
DOI: 10.1016/S0304-4076(97)00083-3
author: Donald W. K. Andrews
published in: Journal of Econometrics
publication date: 2000-10-18T00:00:00Z
review text: The paper considers tests of hypothethes in parametric models in which the parameter of interest is restricted under the alternative hypothesis. As examples of hypotheses of this type can be considered multivariate one-sided hypotheses, joint one- and two-sided hypotheses, and multivariate non-negativity hypotheses. The focus of the paper is on the choice and optimality properties of test statistics. The author specifies a weighted average power optimality criterion and derives tests that are optimal or asymptotically optimal according to this criterion. Exact results are established first for Gaussian linear regression models with known variance and for dynamic nonlinear models the analogical asymptotic properties are derived. The theoretical results outlined above are supplemented by simulation results.
Mathematics Subject Classification ID: 62F03
Mathematics Subject Classification ID: 62F30
Mathematics Subject Classification ID: 62P20
zbMATH DE Number: 1124515
zbMATH Keywords: directed tests
zbMATH Keywords: linear regression
zbMATH Keywords: nonlinear models
zbMATH Keywords: one-sided alternatives
zbMATH Keywords: optimal tests
zbMATH Keywords: weighted average power
MaRDI profile type: Publication
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full work available at URL: s0304-4076(97)00083-3
OpenAlex ID: W2065376442
description: scientific article; zbMATH DE number 1124515