Minimax bias-robust estimation of the dispersion matrix of a multivariate distribution
Adrover, Jorge G.
Ann. Statist., Tome 26 (1998) no. 3, p. 2301-2320 / Harvested from Project Euclid
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Maronna defines affine equivariant $M$-estimators for multivariate location and scatter. They are particularly suited for estimating the pseudo-covariance or scatter matrix of an elliptical population. By defining the bias of a dispersion matrix properly, we consider the maximum bias of an $M$-estimator over an $\varepsilon$ -neighborhood of the underlying elliptical distribution (location known). We find that Tyler’s estimator minimizes the maximum bias.
Publié le : 1998-12-14
Classification:  Bias,  covariance matrix,  elliptical distribution,  $M$-estimation,  mini-max estimation,  multivariate scatter,  pseudocovariance matrix,  robustness,  62H12,  62H10,  62G05 
@article{1024691472,
     author = {Adrover, Jorge G.},
     title = {Minimax bias-robust estimation of the dispersion matrix of a
		 multivariate distribution},
     journal = {Ann. Statist.},
     volume = {26},
     number = {3},
     year = {1998},
     pages = { 2301-2320},
     language = {en},
     url = {http://dml.mathdoc.fr/item/1024691472}
}

Adrover, Jorge G. Minimax bias-robust estimation of the dispersion matrix of a
		 multivariate distribution. Ann. Statist., Tome 26 (1998) no. 3, pp.  2301-2320. http://gdmltest.u-ga.fr/item/1024691472/