<p>This paper addresses the problem of estimating the finite population mean <InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="13370_2024_1234_Article_IEq1.gif" Format="GIF" Height="17" Rendition="HTML" Resolution="72" Type="Linedraw" Width="15" /> </InlineMediaObject> <EquationSource Format="TEX">\(\overline{Y}\)</EquationSource> <EquationSource Format="MATHML"><math> <mover> <mi>Y</mi> <mo>¯</mo> </mover> </math></EquationSource> </InlineEquation> of the study variable <InlineEquation ID="IEq2"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="13370_2024_1234_Article_IEq2.gif" Format="GIF" Height="12" Rendition="HTML" Resolution="72" Type="Linedraw" Width="13" /> </InlineMediaObject> <EquationSource Format="TEX">\(y\)</EquationSource> <EquationSource Format="MATHML"><math> <mi>y</mi> </math></EquationSource> </InlineEquation> using two auxiliary variables in systematic sampling. We have suggested a difference-type estimator and its improved version, and then their properties have been studied. It has been shown that the proposed class of estimators is more efficient than the recently proposed estimators due to Tailor et al. (Stat Transit 14: 391–398, 2013) and Khan and Singh (J Prob Stat <a href="https://doi.org/10.1155/2015/248374">https://doi.org/10.1155/2015/248374</a>, 2015). An empirical study has been undertaken to evaluate the performance of the suggested estimator over other existing estimators.</p>

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An efficient estimation of finite population mean through difference estimator in systematic sampling

  • Surya K. Pal,
  • Sagir A. Mahmud,
  • Housila P. Singh

摘要

This paper addresses the problem of estimating the finite population mean \(\overline{Y}\) Y ¯ of the study variable \(y\) y using two auxiliary variables in systematic sampling. We have suggested a difference-type estimator and its improved version, and then their properties have been studied. It has been shown that the proposed class of estimators is more efficient than the recently proposed estimators due to Tailor et al. (Stat Transit 14: 391–398, 2013) and Khan and Singh (J Prob Stat https://doi.org/10.1155/2015/248374, 2015). An empirical study has been undertaken to evaluate the performance of the suggested estimator over other existing estimators.