Dual divergence estimators and tests: Robustness results

Authors:
Aida Toma;Michel Broniatowski
Affiliations:
Mathematics Department, Academy of Economic Studies, Piaa Roman 6, Bucharest, Romania and "Gheorghe Mihoc-Caius Iacob" Institute of Mathematical Statistics and Applied Mathematics, Calea 13 Septem ...;LSTA, Université Paris 6, 175 Rue du Chevaleret, 75013 Paris, France
Venue:
Journal of Multivariate Analysis
Year:
2011

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Abstract

The class of dual @f-divergence estimators (introduced in Broniatowski and Keziou (2009) [5]) is explored with respect to robustness through the influence function approach. For scale and location models, this class is investigated in terms of robustness and asymptotic relative efficiency. Some hypothesis tests based on dual divergence criteria are proposed and their robustness properties are studied. The empirical performances of these estimators and tests are illustrated by Monte Carlo simulation for both non-contaminated and contaminated data.