Bayesian inference for the Errors-In-Variables model |
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| Authors: | Xing Fang Bofeng Li Hamza Alkhatib Wenxian Zeng Yibin Yao |
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| Institution: | 1.School of Geodesy and Geomatics,Wuhan University,Wuhan,China;2.School of Earth Science,Ohio State University,Columbus,USA;3.College of Surveying and Geo-Informatics,Tongji University,Shanghai,China;4.Geodetic Institute,Leibniz University,Hannover,Germany |
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| Abstract: | 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. |
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