ESTIMATION OF A STRUCTURAL LINEAR-REGRESSION MODEL WITH A KNOWN RELIABILITY RATIO

被引：15

作者：

BOLFARINE, H

CORDANI, LK

机构：

[1] Departamento de Estatistica, Universidade de São Paulo, CEP 01452-990-SP

来源：

ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS | 1993年 / 45卷 / 03期

关键词：

ORTHOGONALITY; PROFILE LIKELIHOOD; MEASUREMENT ERROR MODEL; CONDITIONAL MODEL; LIKELIHOOD RATIO STATISTIC; MARGINAL POSTERIOR DISTRIBUTION;

D O I：

10.1007/BF00773353

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 consider the estimation of the slope parameter beta of a simple structural linear regression model when the reliability ratio (Fuller (1987), Measurement Error Models, Wiley, New York) is considered to be known. By making use of an orthogonal transformation of the unknown parameters, the maximum likelihood estimator of beta and its asymptotic distribution are derived. Likelihood ratio statistics based on the profile and on the conditional profile likelihoods are proposed. An exact marginal posterior distribution of beta, which is shown to be a t-distribution is obtained. Results of a small Monte Carlo study are also reported.

引用

页码：531 / 540

页数：10

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