We investigate the asymptotic behavior of a weighted sample mean and covariance, where the weights are determined by the Mahalanobis distances with respect to initial robust estimators. We derive an explicit expansion for the weighted estimators. From this expansion it can be seen that reweighting does not improve the rate of convergence of the initial estimators. We also show that if one uses smooth S-estimators to deter-mine the weights, the weighted estimators are asymptotically normal. Fi-nally, we will compare the efficiency and local robustness of the reweighted S-estimators with two other improvements of S-estimators: τ-estimators and constrained M-estimators. 1. Introduction. Let X1X
An S-estimator of multivariate location and scale minimizes the determinant of the covariance matrix...
Mahalanobis-type distances in which the shape matrix is derived from a consistent, high-breakdown ro...
Considering two random variables with different laws to which we only have access through finite siz...
We investigate the asymptotic behavior of a weighted sample mean and covariance, where the weights a...
We investigate the asymptotic behavior ofa weighted sample mean and covariance, where the weights ar...
AbstractThis article proposes a reweighted estimator of multivariate location and scatter, with weig...
The iteratively reweighting algorithm is one of the widely used algorithm to compute the M-estimates...
We deal with the equivariant estimation of scatter and location for p-dimensional data, giving empha...
In this paper we introduce weighted estimators of the location and dispersion of a multivariate data...
This article derives the influence function of the Stahel-Donoho estimator of multivariate location ...
Mahalanobis-type distances in which the shape matrix is derived from a consistent, high-breakdown ro...
International audienceThe joint estimation of means and scatter matrices is often a core problem in ...
We discuss the relation between S-estimators and M-estimators of multivariate location and covarianc...
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAM...
International audienceConsidering two random variables with different laws to which we only have acc...
An S-estimator of multivariate location and scale minimizes the determinant of the covariance matrix...
Mahalanobis-type distances in which the shape matrix is derived from a consistent, high-breakdown ro...
Considering two random variables with different laws to which we only have access through finite siz...
We investigate the asymptotic behavior of a weighted sample mean and covariance, where the weights a...
We investigate the asymptotic behavior ofa weighted sample mean and covariance, where the weights ar...
AbstractThis article proposes a reweighted estimator of multivariate location and scatter, with weig...
The iteratively reweighting algorithm is one of the widely used algorithm to compute the M-estimates...
We deal with the equivariant estimation of scatter and location for p-dimensional data, giving empha...
In this paper we introduce weighted estimators of the location and dispersion of a multivariate data...
This article derives the influence function of the Stahel-Donoho estimator of multivariate location ...
Mahalanobis-type distances in which the shape matrix is derived from a consistent, high-breakdown ro...
International audienceThe joint estimation of means and scatter matrices is often a core problem in ...
We discuss the relation between S-estimators and M-estimators of multivariate location and covarianc...
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAM...
International audienceConsidering two random variables with different laws to which we only have acc...
An S-estimator of multivariate location and scale minimizes the determinant of the covariance matrix...
Mahalanobis-type distances in which the shape matrix is derived from a consistent, high-breakdown ro...
Considering two random variables with different laws to which we only have access through finite siz...