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Erschienen in:
1989 | OriginalPaper | Buchkapitel
Shrinking Techniques for Robust Regression
verfasst von : Richard L. Schmoyer, Steven F. Arnold
Erschienen in: Contributions to Probability and Statistics
Verlag: Springer New York
Enthalten in: Professional Book Archive
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The asymptotic normality of robust estimators suggests that shrinking techniques previously considered for least squares regression are appropriate in robust regression as well. Moreover, the noisy nature of the data frequently encountered in robust regression problems makes the use of shrinking estimators particularly advantageous. Asymptotic and finite sample results and a short simulation demonstrate that shrinking techniques can indeed improve a robust estimator’s performance.