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  • 标题:Estimation of Population Variance in Two-Phase Sampling in Presence of Random Non-Response
  • 本地全文:下载
  • 作者:Arnab Bandyopadhyay ; Garib Nath Singh
  • 期刊名称:Pakistan Journal of Statistics and Operation Research
  • 印刷版ISSN:2220-5810
  • 出版年度:2015
  • 卷号:11
  • 期号:4
  • 页码:525-542
  • DOI:10.18187/pjsor.v11i4.1028
  • 语种:English
  • 出版社:College of Statistical and Actuarial Sciences
  • 摘要:The present investigation deals with the problem of estimation of population variance in presence of random non-response in two-phase (double) sampling. Using information on two auxiliary variables, two general classes of estimators have been suggested in two different situations of random non-response and studied their properties under two different set up of two-phase sampling. It is shown that several estimators may be generated from our proposed classes of estimators. Proposed classes of estimators are empirically compared with some contemporary estimators of population variance under the similar realistic situations and their performances have been demonstrated through numerical illustration and graphical interpretation which are followed by suitable recommendations.
  • 其他摘要:The present investigation deals with the problem of estimation of population variance in presence of random non-response in two-phase (double) sampling. Using information on two auxiliary variables, two general classes of estimators have been suggested in two different situations of random non-response and studied their properties under two different set up of two-phase sampling. It is shown that several estimators may be generated from our proposed classes of estimators. Proposed classes of estimators are empirically compared with some contemporary estimators of population variance under the similar realistic situations and their performances have been demonstrated through numerical illustration and graphical interpretation which are followed by suitable recommendations.
  • 关键词:Variance estimation; Two-phase sampling; random non-response; study variable; auxiliary variable; bias; mean square error
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