Use of prior information in the consistent estimation of regression coefficients in measurement error models

JOURNAL OF MULTIVARIATE ANALYSIS

卷:100

Article

Shalabh¹  Garg, Gaurav²  Misra, Neeraj¹ 

[1] Indian Inst Technol, Dept Math & Stat, Kanpur 208016, Uttar Pradesh, India

[2] Jaypee Univ Informat Technol, Dept Math, Solan 173215, HP, India

关键词: Measurement errors;    Exact linear restriction;    Ultrastructural model;    Reliability matrix;    Lowner ordering;   

DOI  :  10.1016/j.jmva.2008.12.014

来源: Elsevier

【 摘 要 】

A multivariate ultrastructural measurement error model is considered and it is assumed that some prior information is available in the form of exact linear restrictions on regression coefficients. Using the prior information along with the additional knowledge of covariance matrix of measurement errors associated with explanatory vector and reliability matrix, we have proposed three methodologies to construct the consistent estimators which also satisfy the given linear restrictions. Asymptotic distribution of these estimators is derived when measurement errors and random error component are not necessarily normally distributed. Dominance conditions for the superiority of one estimator over the other under the criterion of Lowner ordering are obtained for each case of the additional information. Some conditions are also proposed under which the use of a particular type of information will give a more efficient estimator. (c) 2008 Elsevier Inc. All rights reserved.

【 授权许可】

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