We propose an affine equivariant estimator of multivariate location that combines a high breakdown point and a bounded influence function with high asymptotic efficiency. This proposal is basically a location $M$-estimator based on the observations obtained after scaling with an affine equivariant high breakdown covariance estimator. The resulting location estimator will inherit the breakdown point of the initial covariance estimator and within the location-covariance model only the $M$-estimator will determine the type of influence function and the asymptotic behaviour. We prove consistency and asymptotic normality and obtain the breakdown point and the influence function
AbstractA finite sample performance measure of multivariate location estimators is introduced based ...
We consider S-estimators of multivariate location and common dispersion matrix in multiple populatio...
We investigate the performance of robust estimates of multivariate location under nonstandard data c...
We propose an affine equivariant estimator of multivariate location that combines a high breakdown p...
Finite-sample replacement breakdown points are derived for different types of estimators of multivar...
The univariate median is a well-known location estimator, which is √n-consistent, asymptotically Gau...
An affine equivariant estimate of multivariate location based on an adaptive transformation and retr...
AbstractApplying the non-singular affine transformations AZ + μ to a spherically symmetrically distr...
A good robust functional should, if possible, be efficient at the model, smooth, and have a high bre...
Several equivariant estimators of multivariate location and scatter are studied, which are highly ro...
Visuri, Koivunen and Oja (2003) proposed and illustrated the use of the affine equivariant rank cova...
Univariate median is a well-known location estimator, which is√ n-consistent, asymptotically Gaussia...
AbstractThe maximum asymptotic bias of an estimator is a global robustness measure of its performanc...
For the problem of robust estimation of multivariate location and shape, defilllng S-estimators usin...
We discuss the relation between S-estimators and M-estimators of multivariate location and covarianc...
AbstractA finite sample performance measure of multivariate location estimators is introduced based ...
We consider S-estimators of multivariate location and common dispersion matrix in multiple populatio...
We investigate the performance of robust estimates of multivariate location under nonstandard data c...
We propose an affine equivariant estimator of multivariate location that combines a high breakdown p...
Finite-sample replacement breakdown points are derived for different types of estimators of multivar...
The univariate median is a well-known location estimator, which is √n-consistent, asymptotically Gau...
An affine equivariant estimate of multivariate location based on an adaptive transformation and retr...
AbstractApplying the non-singular affine transformations AZ + μ to a spherically symmetrically distr...
A good robust functional should, if possible, be efficient at the model, smooth, and have a high bre...
Several equivariant estimators of multivariate location and scatter are studied, which are highly ro...
Visuri, Koivunen and Oja (2003) proposed and illustrated the use of the affine equivariant rank cova...
Univariate median is a well-known location estimator, which is√ n-consistent, asymptotically Gaussia...
AbstractThe maximum asymptotic bias of an estimator is a global robustness measure of its performanc...
For the problem of robust estimation of multivariate location and shape, defilllng S-estimators usin...
We discuss the relation between S-estimators and M-estimators of multivariate location and covarianc...
AbstractA finite sample performance measure of multivariate location estimators is introduced based ...
We consider S-estimators of multivariate location and common dispersion matrix in multiple populatio...
We investigate the performance of robust estimates of multivariate location under nonstandard data c...