Artículo

Continuity and differentiability of regression M functionals

Fasano, Maria Victoria Icon; Maronna, Ricardo Antonio ; Sued, Raquel Mariela Icon; Yohai, Victor Jaime Icon

Otros responsables

Fecha

11/2012

Editorial

Institute of Mathematical Statistics

Revista

Bernoulli - Mathematical Statistics And Probability

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Institución organizadora

ISSN

1350-7265

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Inglés

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Clasificación temática

Resumen

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 MMestimates are asymptotically normal when the observations are φ-mixing.

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