On linear regression and ratio-product estimation of a finite population mean

Housila P. Singh & Mariano Ruiz Espejo

Journal of the Royal Statistical Society, Series D (The Statistician)2003https://doi.org/10.1111/1467-9884.00341article
ABDC A
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0.39

Abstract

Summary. We consider a class of ratio–product estimators for estimating a finite population mean. The asymptotically optimum estimator in the class is identified, along with its approximate mean-square error. This estimator requires prior knowledge of the parameter C=ρCy/Cx, where ρ is the correlation coefficient between the study variate y and the auxiliary variate x, and Cy and Cx are coefficients of variation of y and x respectively. If C is unknown in advance, then it can be replaced by its consistent estimate , with the resulting estimator known as an ‘estimator based on the estimating optimum’. It is shown that, to the first order of approximation, both estimators have the same mean-square error, and that they are generally more efficient than the usual ratio and product estimators.

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https://doi.org/https://doi.org/10.1111/1467-9884.00341

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@article{housila2003,
  title        = {{On linear regression and ratio-product estimation of a finite population mean}},
  author       = {Housila P. Singh & Mariano Ruiz Espejo},
  journal      = {Journal of the Royal Statistical Society, Series D (The Statistician)},
  year         = {2003},
  doi          = {https://doi.org/https://doi.org/10.1111/1467-9884.00341},
}

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M · momentum0.80 × 0.15 = 0.12
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