Dual divergence estimators and tests: Robustness results

JOURNAL OF MULTIVARIATE ANALYSIS

卷:102

Article

Toma, Aida^1,2  Broniatowski, Michel³ 

[1] Acad Econ Studies, Dept Math, Bucharest, Romania

[2] Gheorghe Mihoc Caius Iacob Inst Math Stat & Appl, Bucharest, Romania

[3] Univ Paris 06, LSTA, F-75013 Paris, France

关键词: Location model;    Minimum divergence estimators;    Robust estimation;    Robust test;    Scale model;   

DOI  :  10.1016/j.jmva.2010.07.010

来源: Elsevier

【 摘 要 】

The class of dual phi-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. (C) 2010 Elsevier Inc. All rights reserved.

【 授权许可】

Free