Robust weighted orthogonal regression in the errors-in-variables model
This paper focuses on robust estimation in the structural errors-in-variables (EV) model. A new class of robust estimators, called weighted orthogonal regression estimators, is introduced. Robust estimators of the parameters of the EV model are simply derived from robust estimators of multivariate location and scatter such as the M-estimators, the S-estimators and the MCD estimator. The influence functions of the proposed estimators are calculated and shown to be bounded. Moreover, we derive the asymptotic distributions of the estimators and illustrate the results on simulated examples and on a real-data set.
Year of publication: |
2004
|
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Authors: | Fekri, M. ; Ruiz-Gazen, A. |
Published in: |
Journal of Multivariate Analysis. - Elsevier, ISSN 0047-259X. - Vol. 88.2004, 1, p. 89-108
|
Publisher: |
Elsevier |
Keywords: | Errors-in-variables model General least squares Robustness Influence function M-estimators S-estimators MCD estimator |
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