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Minimum Disparity Estimation for Normal Models: Small Sample Efficiency
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 Title & Authors
Minimum Disparity Estimation for Normal Models: Small Sample Efficiency
Cho M. J.; Hong C. S.; Jeong D. B.;
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The minimum disparity estimators introduced by Lindsay and Basu (1994) are studied empirically. An extensive simulation in this paper provides a location estimate of the small sample and supplies empirical evidence of the estimator performance for the univariate contaminated normal model. Empirical results show that the minimum generalized negative exponential disparity estimator (MGNEDE) obtains high efficiency for small sample sizes and dominates the maximum likelihood estimator (MLE) and the minimum blended weight Hellinger distance estimator (MBWHDE) with respect to efficiency at the contaminated model.
Disparity measure;Efficiency;Minimum Hellinger distance estimator;Minimum negative exponential disparity estimator;Newton-Raphson method;
 Cited by
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