AbstractIn this paper we derive the change-of-variance function of M-estimators of scale under general contamination, thereby extending the formula in Hampel et al. (1986). We say that an M-estimator is B-robust if its influence function is bounded, and we call it V-robust if its change-of-variance function is bounded from above. It is shown, for a natural class of M-estimators, that the general notion of V-robustness still implies B-robustness. Several classes of M-estimators are studied closely, as well as some typical examples and their interpretation
AbstractThe influence curve (JC) of a Fisher-consistent functional was introduced by F. Hampel and p...
Robust estimates of the scale parameter characterizing the spread of a random variable are studied i...
A reasonable approach to robust regression estimation is minimizing a robust scale estimator of the...
AbstractIn this paper we derive the change-of-variance function of M-estimators of scale under gener...
In this paper we derive the change-of-variance function of M-estimators of scale under general conta...
AbstractWe investigate optimal bounded influence M-estimators in the general normal regression model...
Generalized Linear Models extends classical regression models to non-normal response variables and a...
We investigate optimal bounded influence M-estimators in the general normal regression model with re...
By means of the concept of change-of-variance function we investigate the stability properties of th...
The field of Robust Statistics deals with the problem of stability of estimators under a certain typ...
The change-of-variance function is defined for estimators of regression coefficients. Both an unstan...
AbstractLet (X1, Y1),…, (Xn, Yn) be i.i.d. rv's and let m(x) = E(Y|X = x) be the regression curve of...
AbstractWe discuss the asymptotic linearization of multivariate M-estimators, when the limit distrib...
LA _ The view, opinions, and/or findings contained in this report are C.6i those of the author(s) an...
Let (X1, Y1),..., (Xn, Yn) be i.i.d. rv's and let m(x) = E(YX = x) be the regression curve of Y on X...
AbstractThe influence curve (JC) of a Fisher-consistent functional was introduced by F. Hampel and p...
Robust estimates of the scale parameter characterizing the spread of a random variable are studied i...
A reasonable approach to robust regression estimation is minimizing a robust scale estimator of the...
AbstractIn this paper we derive the change-of-variance function of M-estimators of scale under gener...
In this paper we derive the change-of-variance function of M-estimators of scale under general conta...
AbstractWe investigate optimal bounded influence M-estimators in the general normal regression model...
Generalized Linear Models extends classical regression models to non-normal response variables and a...
We investigate optimal bounded influence M-estimators in the general normal regression model with re...
By means of the concept of change-of-variance function we investigate the stability properties of th...
The field of Robust Statistics deals with the problem of stability of estimators under a certain typ...
The change-of-variance function is defined for estimators of regression coefficients. Both an unstan...
AbstractLet (X1, Y1),…, (Xn, Yn) be i.i.d. rv's and let m(x) = E(Y|X = x) be the regression curve of...
AbstractWe discuss the asymptotic linearization of multivariate M-estimators, when the limit distrib...
LA _ The view, opinions, and/or findings contained in this report are C.6i those of the author(s) an...
Let (X1, Y1),..., (Xn, Yn) be i.i.d. rv's and let m(x) = E(YX = x) be the regression curve of Y on X...
AbstractThe influence curve (JC) of a Fisher-consistent functional was introduced by F. Hampel and p...
Robust estimates of the scale parameter characterizing the spread of a random variable are studied i...
A reasonable approach to robust regression estimation is minimizing a robust scale estimator of the...