Enhancing the Mean Ratio Estimators for Estimating Population Mean Using Non-Conventional Location Parameters

• MUHAMMAD ABID ^[1] ; Nasir Abbas ; HAFIZ ZAFAR NAZIR ^[2] ; ZHENGYAN LIN ^[1]
  1. [1] Zhejiang University

     Zhejiang University

     China

     
  2. [2] University of Sargodha

     University of Sargodha

     Pakistán

     
  3. [3] Government College University Faculty of Science And Technology Department of Statistics

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• Localización: Revista Colombiana de Estadística, ISSN-e 2389-8976, ISSN 0120-1751, Vol. 39, Nº. 1, 2016, págs. 63-79
• Idioma: inglés
• DOI: 10.15446/rce.v39n1.55139
• Títulos paralelos:
  • Mejoras a los estimadores de razón de medias con el fin de estimar la media poblacional usando parámetros de localización no convencionales
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  • Texto completo
• Resumen
  • español

    Las medidas convencionales de localización son a menudo usadas con el fin de desarrollar estimatores de raz ón. Sin embargo, en este artículo, se hace un intento por usar algunas medidas de localización no convencionales. Se incorpora la trimean, el estimador de Hodges-Lehmann y el rango medio de la variable auxiliar con este propósito. Para mejorar la eficiencia de los estimadores de razón de medias propuestos, el coeficiente de correlación poblacional, el coeficiente de variación y combinaciones lineales de variables auxiliares también han sido explotados. Las propiedades asociadas con los estimadores propuestos son evaluadas a través del sesgo y el error cuadrático medio. Un studio empírico es presentado con fines de ilustración y verificación.

  • English

    Conventional measures of location are commonly used to develop ratio estimators. However, in this article, we attempt to use some non-conventional location measures. We have incorporated tri-mean, Hodges-Lehmann, and mid-range of the auxiliary variable for this purpose. To enhance the efficiency of the proposed mean ratio estimators, population correlation coefficient, coefficient of variation and the linear combinations of auxiliary variable have also been exploited. The properties associated with the proposed estimators are evaluated through bias and mean square errors. We also provide an empirical study for illustration and verification.

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