Bayesian inference for the Errors-In-Variables model

详细信息    查看全文

• 作者：Xing Fang ; Bofeng Li ; Hamza Alkhatib ; Wenxian Zeng…
• 关键词：Errors ; In ; Variables ; Total Least ; Squares ; Bayesian inference ; quasi solution ; Maximum Likelihood ; noninformative prior ; informative prior
• 刊名：Studia Geophysica et Geodaetica
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：61
• 期：1
• 页码：35-52
• 全文大小：
• 刊物类别：Earth and Environmental Science
• 刊物主题：Geophysics/Geodesy; Structural Geology; Atmospheric Sciences;
• 出版者：Springer Netherlands
• ISSN：1573-1626
• 卷排序：61

文摘

We discuss the Bayesian inference based on the Errors-In-Variables (EIV) model. The proposed estimators are developed not only for the unknown parameters but also for the variance factor with or without prior information. The proposed Total Least-Squares (TLS) estimators of the unknown parameter are deemed as the quasi Least-Squares (LS) and quasi maximum a posterior (MAP) solution. In addition, the variance factor of the EIV model is proven to be always smaller than the variance factor of the traditional linear model. A numerical example demonstrates the performance of the proposed solutions.