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

Janusz L. Wywiał ()

Statistics in Transition new series, 2011, vol. 12, issue 1, 127-138

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.

Keywords: sampling design; order statistic; auxiliary variable; sampling scheme; Horvitz-Thompson estimator; small area estimation; area sampling; depth function (search for similar items in EconPapers)
Date: 2011
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Persistent link: https://EconPapers.repec.org/RePEc:csb:stintr:v:12:y:2011:i:1:p:127-138

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