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Bayesian inference for the Errors-In-Variables model

verfasst von
Xing Fang, Bofeng Li, Hamza Alkhatib, Wenxian Zeng, Yibin Yao
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.

Organisationseinheit(en)
Geodätisches Institut
Externe Organisation(en)
Wuhan University
The Ohio State University
Tongji University
Typ
Artikel
Journal
Studia geophysica et geodaetica
Band
61
Seiten
35-52
Anzahl der Seiten
18
ISSN
0039-3169
Publikationsdatum
01.2017
Publikationsstatus
Veröffentlicht
Peer-reviewed
Ja
ASJC Scopus Sachgebiete
Geophysik, Geochemie und Petrologie
Elektronische Version(en)
https://doi.org/10.1007/s11200-015-6107-9 (Zugang: Geschlossen)
 

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