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Estimation of domain means on the basis of strategy dependent on depth function of auxiliary variables` distribution

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  • Janusz L. Wywiał

Abstract

The paper deals with the problem of estimation of a domain means in a finite and fixed population. We assume that observations of a multidimensional auxiliary variable are known in the population. The proposed estimation strategy consists of the well known Horvitz-Thompson estimator and the non-simple sampling design dependent on a synthetic auxiliary variable whose observations are equal to the values of a depth function of the auxiliary variable distribution. The well known spherical and Mahalanobis depth functions are considered. A sampling design is proportionate to the maximal order statistic determined on the basis of the synthetic auxiliary variable observations in a simple sample drawn without replacement. A computer simulation analysis leads to the conclusion that the proposed estimation strategy is more accurate for domain means than the well known simple sample means.

Suggested Citation

  • Janusz L. Wywiał, 2011. "Estimation of domain means on the basis of strategy dependent on depth function of auxiliary variables` distribution," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 12(1), pages 127-138, August.
    • Handle: RePEc:csb:stintr:v:12:y:2011:i:1:p:127-138
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    References listed on IDEAS

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    1. Janusz Wywiał, 2008. "Sampling design proportional to order statistic of auxiliary variable," Statistical Papers, Springer, vol. 49(2), pages 277-289, April.
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