Dual divergence estimators and tests: Robustness results

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Dual divergence estimators and tests: Robustness results
The class of dual φ-divergence estimators (introduced in Broniatowski and Keziou (2009) [6]) 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 criterions are proposed and their robustness properties are studied. The empirical performances of these estimators and tests are illustrated by Monte Carlo simulation for both noncontaminated and contaminated data. Key words: Location model, minimum divergence estimators, robust estimation, robust test, scale model
Aida Toma, Michel Broniatowski
Added 14 May 2011
Updated 14 May 2011
Type Journal
Year 2011
Where MA
Authors Aida Toma, Michel Broniatowski
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