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  <titleInfo>
    <title>ESTIMATION  OF  THE  MEAN  OF  THE  EXPONENTIAL  DISTRIBUTIONUSING  EXTREME RANKED  SET SAMPLING  WITH UNEQUAL  SAMPLES</title>
  </titleInfo>
  <name type="personal">
    <namePart>Biradar, B.S.</namePart>
    <role>
      <roleTerm authority="marcrelator" type="text">creator</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Santosha, C.D.</namePart>
  </name>
  <typeOfResource>text</typeOfResource>
  <originInfo>
    <place>
      <placeTerm type="code" authority="marccountry">xx</placeTerm>
    </place>
    <dateIssued>2017</dateIssued>
    <dateIssued encoding="marc">9999</dateIssued>
    <issuance>monographic</issuance>
  </originInfo>
  <language>
    <languageTerm authority="iso639-2b" type="code">und</languageTerm>
  </language>
  <physicalDescription>
    <form authority="marcform">print</form>
    <extent>393-401</extent>
  </physicalDescription>
  <abstract>In many environmental studies, the main focus is on observational economy, that is to obtain data on the basis ofcost effective and efficient sampling methods. In this paper, a ranked set sampling procedure with unequal samples based onextremes (ERSSU) is proposed, which reduces the cost and increases the precision of the estimator. Maximum likelihoodestimator and modified maximum likelihood estimators are obtained and their properties are studied when the underlyingdistribution is exponential. These methods are studied under both perfect and imperfect ranking (with errors in ranking).These estimators are then compared with estimators based on simple random sampling (SRS) and ranked set sampling (RSS)procedures. It is shown that relative efficiencies of the estimators based on ERSSU are better than those of the estimatorbased on SRS. Simulation results show that efficiency of proposed estimator is better than estimators based on SRS and RSS,when errors in ranking are present</abstract>
  <subject>
    <topic>Ranked set sampling, Extreme ranked set sampling, Maximum likelihood estimator, Modified maximum likelihoodestimator, Errors in ranking, Efficiency</topic>
  </subject>
  <relatedItem type="host">
    <name>
      <namePart>International Journal of Agricultural Statistical Science</namePart>
    </name>
  </relatedItem>
  <identifier type="issn">0973-1903</identifier>
  <recordInfo>
    <recordCreationDate encoding="marc">210629</recordCreationDate>
  </recordInfo>
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