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Estimation of the mean of the exponential distribution using moving extremes ranked set sampling

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Abstract

Moving Extremes Ranked Set Sampling (MERSS) is a useful modification of Ranked Set Sampling (RSS). Unlike RSS, MERSS allows for an increase of set size without introducing too much ranking error. The method is considered parametrically under exponential distribution. Maximum likelihood estimator (MLE), and a modified MLE are considered and their properties are studied. The method is studied under both perfect and imperfect ranking (with error in ranking). It appears that these estimators can be real competitors to the MLE using the usual simple random sampling (SRS).

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Authors and Affiliations

  1. Department of Statistics, Yarmouk University, Yarmouk, Jordan

    Mohammad Fraiwan Al-Saleh

  2. Department of Mathematics and Statistics, Sultan Qaboos University, Oman, Oman

    Said Ali Al-Hadhrami

Authors
  1. Mohammad Fraiwan Al-Saleh
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  2. Said Ali Al-Hadhrami
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Correspondence to Mohammad Fraiwan Al-Saleh.

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Al-Saleh, M.F., Al-Hadhrami, S.A. Estimation of the mean of the exponential distribution using moving extremes ranked set sampling. Statistical Papers 44, 367–382 (2003). https://doi.org/10.1007/s00362-003-0161-z

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  • DOI: https://doi.org/10.1007/s00362-003-0161-z

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