Testing for and against a set of inequality constraints: The k-sample case

被引：1

作者：

Elbarmi, Hammou ^{[1
]}

Nunez-Anton, Vicente ^{[2
]}

Zimmerman, Dale L. ^{[3
]}

机构：

[1] CUNY, Baruch Coll, Dept Stat & CIS, New York, NY 10021 USA

[2] Univ Basque Country, Dept Econometria & Estadist EA 3, E-48080 Bilbao, Spain

[3] Univ Iowa, Dept Stat & Actuarial Sci, Iowa City, IA 52242 USA

来源：

JOURNAL OF STATISTICAL PLANNING AND INFERENCE | 2009年 / 139卷 / 03期

关键词：

Chi-bar square; Inequality constraints; Lagrange multipliers; Likelihood ratio; Orthant probabilities; MAXIMUM-LIKELIHOOD-ESTIMATION; FENCHEL DUALITY;

D O I：

10.1016/j.jspi.2008.06.008

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

In this paper we aim to generalize the existing results and provide a test for testing for and against a set of inequality constraints placed upon any k (k >= I) vectors of parameters corresponcling to k populations. The approach we take is the likelihood ratio approach. We show that the limiting distributions of the likelihood ratio test are of chi-bar square type and provide the expression of the weighting values. Examples are discussed to illustrate the theoretical results. (C) 2008 Elsevier B.V. All rights reserved.

引用

页码：1012 / 1022

页数：11

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