We discuss the relation between S-estimators and M-estimators of multivariate location and covariance. As in the case of the estimation of a multiple regression parameter, S-estimators are shown to satisfy first-order conditions of M-estimators. We show that the influence function IF (x;S F) of S-functionals exists and is the same as that of corresponding M-functionals. Also, we show that S-estimators have a limiting normal distribution which is similar to the limiting normal distribution which is similar to the limiting normal distribution of M-estimators. Finally, we compare asymptotic variances and breakdown point of both types of estimators
We provide a unified approach to S-estimation in balanced linear models with structured covariance m...
AbstractIn this paper we introduce generalized S-estimators for the multivariate regression model. T...
We define the minimum covariance determinant functionals for multivariate location and scatter throu...
We discuss the relation between S-estimators and M-estimators of multivariate location and covarianc...
In this paper we consider S-estimators for multivariate regression. We study the robustness of the e...
In this paper we consider S-estimators for multivariate regression. We study the robustness of the e...
This survey provides a self-contained account of M-estimation of multivariate scatter. In particular...
In this paper we introduce generalized S-estimators for the multivariate regression model. This clas...
In this paper we estimate the parameters of a regression model using S-estimators of multivariate lo...
The minimum covariance determinant (MCD) estimators of multivariate location and scatter are robust ...
In this paper we introduce generalized S-estimators for the multivariate regression model This class...
International audienceThe joint estimation of means and scatter matrices is often a core problem in ...
In this paper we estimate the parameters of a regression model using S-estimators of multivariate lo...
It is shown under appropriate conditions that Rousseeuw's minimum volume estimator and other $S$-est...
We tackle the problem of obtaining the consistency factors of robust S-estimators of location and sc...
We provide a unified approach to S-estimation in balanced linear models with structured covariance m...
AbstractIn this paper we introduce generalized S-estimators for the multivariate regression model. T...
We define the minimum covariance determinant functionals for multivariate location and scatter throu...
We discuss the relation between S-estimators and M-estimators of multivariate location and covarianc...
In this paper we consider S-estimators for multivariate regression. We study the robustness of the e...
In this paper we consider S-estimators for multivariate regression. We study the robustness of the e...
This survey provides a self-contained account of M-estimation of multivariate scatter. In particular...
In this paper we introduce generalized S-estimators for the multivariate regression model. This clas...
In this paper we estimate the parameters of a regression model using S-estimators of multivariate lo...
The minimum covariance determinant (MCD) estimators of multivariate location and scatter are robust ...
In this paper we introduce generalized S-estimators for the multivariate regression model This class...
International audienceThe joint estimation of means and scatter matrices is often a core problem in ...
In this paper we estimate the parameters of a regression model using S-estimators of multivariate lo...
It is shown under appropriate conditions that Rousseeuw's minimum volume estimator and other $S$-est...
We tackle the problem of obtaining the consistency factors of robust S-estimators of location and sc...
We provide a unified approach to S-estimation in balanced linear models with structured covariance m...
AbstractIn this paper we introduce generalized S-estimators for the multivariate regression model. T...
We define the minimum covariance determinant functionals for multivariate location and scatter throu...