Multivariate Linear Error-in-variable Model with Singular Covariance Matrix

被引：0

作者：

Chen, Qingping ^{[1
]}

Huang, Zhiyong ^{[1
]}

机构：

[1] Wuhan Univ Sci & Technol, Wuhan 430081, Peoples R China

来源：

PROCEEDINGS OF THE EIGHTH INTERNATIONAL CONFERENCE ON INFORMATION AND MANAGEMENT SCIENCES | 2009年 / 8卷

关键词：

Multivariate linear model; Error-in-variable; singular covariance matrix; Least squares estimators; Maximum likelihood estimators;

D O I：

暂无

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

In the analysis of the multivariate linear error-invariable model, it is assumed that the covariance matrix is nonsingular. The assumption of nonsingularity limits the number of application in practice. In this paper, we relax the condition of nonsingularity and consider the case when the covariance matrix may be singular. General least squares estimators and maximum likelihood estimators are derived for the singular covariance matrix case. These results can include that in Li and Tang(2006).

引用

页码：904 / 907

页数：4

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