Communications for Statistical Applications and Methods

  • 제6권3호
  • /
  • Pages.967-976
  • /
  • 1999
  • /
  • 2287-7843(pISSN)
  • /
  • 2383-4757(eISSN)
한국통계학회 (The Korean Statistical Society)
권호 표지

Minimum Hellinger Distance Bsed Goodness-of-fit Tests in Normal Models: Empirical Approach

  • Dong Bin Jeong (Assistant Professor Department of Statistics Kangnug National University)
  • 발행 : 1999.12.01
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초록

In this paper we study the Hellinger distance based goodness-of-fit tests that are analogs of likelihood ratio tests. The minimum Hellinger distance estimator (MHDE) in normal models provides an excellent robust alternative to the usual maximum likelihood estimator. Our simulation results show that the Hellinger deviance test (Simpson 1989) based goodness-of-fit test is robust when data contain outliers. The proposed hellinger deviance test(Simpson 1989) is a more direcct method for obtaining robust inferences than an automated outlier screen method used before the likelihood ratio test data analysis.

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참고문헌

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