The change-of-variance function is defined for estimators of regression coefficients. Both an unstandardized and a standardized form of the change-of-variance sensitivity are introduced, and their relation with the corresponding gross-error-sensitivities is investigated. The problems of optimal robustness lead to the Hampel-Krasker and the Krasker-Welsch estimators. At the same time, also the scale parameter has to be estimated robustly. By means of the change-of-variance sensitivity, optimal robust redescending scale estimators are constructed
We define the change-of-variance curve (CVC) of location M-estimators in order to investigate the in...
Influence curves of some parameters under various methods of factor analysis have been given in the ...
The coefficient of variation is a well-known measure used in many fields to compare the variability ...
We investigate optimal bounded influence M-estimators in the general normal regression model with re...
AbstractWe investigate optimal bounded influence M-estimators in the general normal regression model...
In this paper we derive the change-of-variance function of M-estimators of scale under general conta...
AbstractIn this paper we derive the change-of-variance function of M-estimators of scale under gener...
By means of the concept of change-of-variance function we investigate the stability properties of th...
A statistical sensitivity analysis may be defined and performed in terms of the response of a vector...
The study of the effect of the violations of the model assumptions on the parameter of interest is c...
A reasonable approach to robust regression estimation is minimizing a robust scale estimator of the...
Several problems emerging with the studentization of M-estimators of regression model are briefly di...
78 model parameters were varied between -99% to +400% of their default values to identify the maximu...
Variance based methods have assessed themselves as versatile and effective among the various availa...
The R package sensobol provides several functions to conduct variance-based uncertainty and sensitiv...
We define the change-of-variance curve (CVC) of location M-estimators in order to investigate the in...
Influence curves of some parameters under various methods of factor analysis have been given in the ...
The coefficient of variation is a well-known measure used in many fields to compare the variability ...
We investigate optimal bounded influence M-estimators in the general normal regression model with re...
AbstractWe investigate optimal bounded influence M-estimators in the general normal regression model...
In this paper we derive the change-of-variance function of M-estimators of scale under general conta...
AbstractIn this paper we derive the change-of-variance function of M-estimators of scale under gener...
By means of the concept of change-of-variance function we investigate the stability properties of th...
A statistical sensitivity analysis may be defined and performed in terms of the response of a vector...
The study of the effect of the violations of the model assumptions on the parameter of interest is c...
A reasonable approach to robust regression estimation is minimizing a robust scale estimator of the...
Several problems emerging with the studentization of M-estimators of regression model are briefly di...
78 model parameters were varied between -99% to +400% of their default values to identify the maximu...
Variance based methods have assessed themselves as versatile and effective among the various availa...
The R package sensobol provides several functions to conduct variance-based uncertainty and sensitiv...
We define the change-of-variance curve (CVC) of location M-estimators in order to investigate the in...
Influence curves of some parameters under various methods of factor analysis have been given in the ...
The coefficient of variation is a well-known measure used in many fields to compare the variability ...