Open Access
November 2012 Continuity and differentiability of regression M functionals
María V. Fasano, Ricardo A. Maronna, Mariela Sued, Víctor J. Yohai
Bernoulli 18(4): 1284-1309 (November 2012). DOI: 10.3150/11-BEJ368

Abstract

This paper deals with the Fisher-consistency, weak continuity and differentiability of estimating functionals corresponding to a class of both linear and nonlinear regression high breakdown M estimates, which includes S and MM estimates. A restricted type of differentiability, called weak differentiability, is defined, which suffices to prove the asymptotic normality of estimates based on the functionals. This approach allows to prove the consistency, asymptotic normality and qualitative robustness of M estimates under more general conditions than those required in standard approaches. In particular, we prove that regression MM-estimates are asymptotically normal when the observations are $\phi$-mixing.

Citation

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María V. Fasano. Ricardo A. Maronna. Mariela Sued. Víctor J. Yohai. "Continuity and differentiability of regression M functionals." Bernoulli 18 (4) 1284 - 1309, November 2012. https://doi.org/10.3150/11-BEJ368

Information

Published: November 2012
First available in Project Euclid: 12 November 2012

zbMATH: 1329.62303
MathSciNet: MR2995796
Digital Object Identifier: 10.3150/11-BEJ368

Keywords: asymptotic normality , consistency , MM estimates , Nonlinear regression , S estimates

Rights: Copyright © 2012 Bernoulli Society for Mathematical Statistics and Probability

Vol.18 • No. 4 • November 2012
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