DOI QR코드

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Minimum Disparity Estimation for Normal Models: Small Sample Efficiency

  • Cho M. J. (Research Institute of Applied Statistics, Sungkyunkwan University) ;
  • Hong C. S. (Department of Statistics, Sungkyunkwan University) ;
  • Jeong D. B. (Department of Information Statistics, Kangnung National University)
  • 발행 : 2005.04.01

초록

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.

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참고문헌

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