Comptes Rendus
no. 9
Statistics/Probability Theory
Bounded influence estimators for multivariate lognormal distributions
[Estimateurs à fonction d'influence bornée pour des lois lognormales multivariées]

Présenté par : Paul Deheuvels

Aida Toma1
1 Mathematics Department, Academy of Economic Studies, Piata Romana no. 6, Bucharest, Romania
Comptes Rendus. Mathématique, Volume 338 (2004) no. 9, pp. 723-728.

Dans cet article, nous considérons le problème de l'estimation robuste de certains paramètres relatifs à une distribution multivariée lognormale. Dans ce but, nous construisons une classe d'estimateurs et donnons certaines de leurs propriétés telles que la consistence au sens de Fisher, la robustesse et la normalité asymptotique.

In this paper we consider the problem of robust estimation of some parameters related to a multivariate lognormal distribution. In this sense, we construct a class of estimators and discuss some of its properties, such as Fisher consistency, robustness and asymptotic normality.

Reçu le :
Accepté le :
Publié le :
DOI : 10.1016/j.crma.2004.02.017
Aida Toma 1

1 Mathematics Department, Academy of Economic Studies, Piata Romana no. 6, Bucharest, Romania 
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Aida Toma. Bounded influence estimators for multivariate lognormal distributions. Comptes Rendus. Mathématique, Volume 338 (2004) no. 9, pp. 723-728. doi : 10.1016/j.crma.2004.02.017. https://comptes-rendus.academie-sciences.fr/mathematique/articles/10.1016/j.crma.2004.02.017/

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[8] R.A. Maronna Robust M-estimators of multivariate location and scatter, Ann. Statist., Volume 4 (1976), pp. 51-67

[9] R.A. Maronna; V. Yohai Robust estimation of multivariate location and scatter (S. Kots; C. Read; D. Banks, eds.), Encyclopedia of Statistical Sciencies, Wiley, 1998

[10] P.J. Rousseeuw Multivariate estimation with high breakdown point (W. Grossmann; G. Pflug; I. Vincze; W. Wertz, eds.), Math. Statist. Appl., vol. B, Reidel, Dodrecht, 1985, pp. 283-297

[11] A. Toma Robust estimators for the parameters of multivariate lognormal distributions, Comm. Statist. Theory Methods, Volume 32 (2003), pp. 1405-1417

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