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| Titel |
Constrained robust estimation of magnetotelluric impedance functions based on a bounded-influence regression M-estimator and the Hilbert transform |
| VerfasserIn |
D. Sutarno |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1023-5809
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| Digitales Dokument |
URL |
| Erschienen |
In: Nonlinear Processes in Geophysics ; 15, no. 2 ; Nr. 15, no. 2 (2008-03-25), S.287-293 |
| Datensatznummer |
250012616
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| Publikation (Nr.) |
 copernicus.org/npg-15-287-2008.pdf |
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| Zusammenfassung |
Robust impedance estimation procedures are now in standard use in
magnetotelluric (MT) measurements and research. These always yield impedance
estimates which are better than the conventional least square (LS)
estimation because the 'real' MT data almost never satisfy the statistical
assumptions of Gaussian distribution upon which normal spectral analysis is
based. The robust estimation procedures are commonly based on M-estimators
that have the ability to reduce the influence of unusual data (outliers) in
the response (electric field) variables, but are often not sensitive to
exceptional predictors (magnetic field) data, which are termed leverage
points.
This paper proposes an alternative procedure for making reliably robust
estimates of MT impedance functions, which simultaneously provide protection
from the influence of outliers in both response and input variables. The
means for accomplishing this is based on the bounded-influence regression
M-estimation and the Hilbert Transform operating on the causal MT impedance
functions. In the resulting regression estimates, outlier contamination is
removed and the self consistency between the real and imaginary parts of the
impedance estimates is guaranteed. Using synthetic and real MT data, it is
shown that the method can produce improved MT impedance functions even under
conditions of severe noise contamination. |
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