Continuity and differentiability of regression M functionals
; Maronna, Ricardo Antonio ; Sued, Raquel Mariela
; Yohai, Victor Jaime 
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Fecha
11/2012
Editorial
Institute of Mathematical Statistics
Revista
Bernoulli - Mathematical Statistics And Probability
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1350-7265
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Inglés
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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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