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Robust Geodetic Parameter Estimation Under Least Squares Through Weighting on the Basis of the Mean Square Error

  • Francis W. O. Aduol
Chapter

Abstract

A technique for the robust estimation of geodetic parameters under the least squares method when weights are specified through the use of the mean square error is presented. The mean square error is considered in the specification of observational weights instead of the conventional approach based on the observational variance. The practical application of the proposed approach is demonstrated through computational examples based on a geodetic network. The results indicate that the least squares estimation with observational weights based on the mean square error is relatively robust against outliers in the observational set, provided the network (or the system) under consideration has a good level of reliability, as to make the network (or system) stable under estimation.

Keywords

Robust Estimation Outlier Detection Observational Error Geodetic Network Outlying Observation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Francis W. O. Aduol

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