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Title: Sensitivity analysis of $M$-estimators of non-linear regression models (English)
Author: Rubio, A. M.
Author: Quintana, F.
Author: Víšek, J. Á.
Language: English
Journal: Commentationes Mathematicae Universitatis Carolinae
ISSN: 0010-2628 (print)
ISSN: 1213-7243 (online)
Volume: 35
Issue: 1
Year: 1994
Pages: 111-125
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Category: math
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Summary: An asymptotic formula for the difference of the $M$-estimates of the regression coefficients of the non-linear model for all $n$ observations and for $n-1$ observations is presented under conditions covering the twice absolutely continuous $\varrho$-functions. Then the implications for the $M$-estimation of the regression model are discussed. (English)
Keyword: $M$-estimation of non-linear regression models
Keyword: the influence points
MSC: 62F12
MSC: 62F35
MSC: 62J02
idZBL: Zbl 0794.62022
idMR: MR1292588
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Date available: 2009-01-08T18:09:19Z
Last updated: 2012-04-30
Stable URL: http://hdl.handle.net/10338.dmlcz/118646
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Reference: Chatterjee S., Hadi A.S.: Sensitivity Analysis in Linear Regression.J. Wiley & Sons, New York. Zbl 0648.62066, MR 0939610
Reference: Cook R.D., Weisberg S.: Residuals and Influence in Regression.Chapman and Hall, New York. Zbl 0564.62054, MR 0675263
Reference: Hampel F.R., Ronchetti E.M., Rousseeuw P.J., Stahel W.A.: Robust Statistics - The Approach Based on Influence Functions.J. Wiley & Sons, New York. Zbl 0733.62038, MR 0829458
Reference: Huber P.J.: A robust version of the probability ratio test.Ann. Math. Statist. 36, 1753-1758. Zbl 0137.12702, MR 0185747
Reference: Víšek J.Á.: Stability of regression model estimates with respect to subsamples.Computational Statistics 7 183-203. MR 1178353
Reference: Welsch R.E.: Influence function and regression diagnostics.In: Modern Data Analysis, R.L. Launer and A.F. Siegel, eds., Academic Press, New York, 149-169.
Reference: Zvára K.: Regression analysis (in Czech).Academia, Prague.
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