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)
