On robustness and efficiency of minimum divergence estimators

• Autores: Raúl Jiménez , Yongzhao Shao
• Localización: Test: An Official Journal of the Spanish Society of Statistics and Operations Research, ISSN-e 1863-8260, ISSN 1133-0686, Vol. 10, Nº. 2, 2001, págs. 241-248
• Idioma: inglés
• DOI: 10.1007/bf02595695
• Texto completo no disponible (Saber más ...)
• Resumen

  • We study the trade-off between efficiency and robustness of the estimators obtained by minimizing the divergence statistics and their adjoins; obtained by minimizing the asymmetric counterparts of the divergence statistics. In particular, it is shown that no minimum power-divergence estimator is better than the minimum Hellinger distance estimator in terms of both second-order efficiency and robustness