info:eu-repo/semantics/article
Continuity and differentiability of regression M functionals
Fecha
2012-11Registro en:
Fasano, Maria Victoria; Maronna, Ricardo Antonio; Sued, Raquel Mariela; Yohai, Victor Jaime; Continuity and differentiability of regression M functionals; Institute of Mathematical Statistics; Bernoulli - Mathematical Statistics And Probability; 18; 4; 11-2012; 1284-1309
1350-7265
CONICET Digital
CONICET
Autor
Fasano, Maria Victoria
Maronna, Ricardo Antonio
Sued, Raquel Mariela
Yohai, Victor Jaime
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.