A Robust Method for Relative Gravity Data Estimation with High Efficiency |
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| Authors: | F Touati M Idres S Kahlouche |
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| Institution: | (1) Geodetic Laboratory, Center of Space Techniques, BP 13, 31200 Arzew, Algeria;(2) Department of Geophysics, University of Science and Technology H.B., BP 32, 16111 Algiers, Algeria |
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| Abstract: | When gravimetric data observations have outliers, using standard least squares (LS) estimation will likely give poor accuracies
and unreliable parameter estimates. One of the typical approaches to overcome this problem consists of using the robust estimation
techniques. In this paper, we modified the robust estimator of Gervini and Yohai (2002) called REWLSE (Robust and Efficient Weighted Least Squares Estimator), which combines simultaneously high statistical efficiency
and high breakdown point by replacing the weight function by a new weight function. This method allows reducing the outlier
impacts and makes more use of the information provided by the data. In order to adapt this technique to the relative gravity
data, weights are computed using the empirical distribution of the residuals obtained initially by the LTS (Least Trimmed
Squares) estimator and by minimizing the mean distances relatively to the LS-estimator without outliers. The robustness of
the initial estimator is maintained by adapted cut-off values as suggested by the REWLSE method which allows also a reasonable
statistical efficiency. Hereafter we give the advantage and the pertinence of REWLSE procedure on real and semi-simulated
gravity data by comparing it with conventional LS and other robust approaches like M- and MM-estimators. |
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