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Sensitivity analysis in Gauss-Markov models

Citation

Ding, X and Coleman, R, Sensitivity analysis in Gauss-Markov models, Journal of Geodesy, 70, (8) pp. 480-488. ISSN 0949-7714 (1996) [Refereed Article]

DOI: doi:10.1007/BF00863620

Abstract

The estimated parameters from a Gauss-Markov model have varying sensitivity to the individual observations included in the model. Similarly, the redundancy contribution (number) of any observation is associated differently to all the other observations in the model. Evaluation of the sensitivity of parameters to observations, and the sensitivity of the redundancy contribution of one observation to the others are useful to gain more insight into Gauss-Markov models. Such analysis has found practical applications in survey network design and in multiple outlier detections. This paper presents some quantitative sensitivity measures for general Gauss-Markov models. The application of the concept in surveying network design is also discussed.

Item Details

Item Type:Refereed Article
Research Division:Engineering
Research Group:Geomatic Engineering
Research Field:Surveying (incl. Hydrographic Surveying)
Objective Division:Expanding Knowledge
Objective Group:Expanding Knowledge
Objective Field:Expanding Knowledge in Philosophy and Religious Studies
Author:Coleman, R (Professor Richard Coleman)
ID Code:7437
Year Published:1996
Web of Science® Times Cited:7
Deposited By:Surveying and Spatial Information Science
Deposited On:1996-08-01
Last Modified:2011-08-19
Downloads:0

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