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Estimating quantiles under sampling on two occasions with arbitrary sample designs

机译:使用任意样本设计两次评估抽样下的分位数

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摘要

A practical problem related to the estimation of quantiles in double sampling with arbitrary sampling designs in each of the two phases is investigated. In practice, this scheme is commonly used for official surveys, in which quantile estimation is often required when the investigation deals with variables such as income or expenditure. A class of estimators for quantiles is proposed and some important properties, such as asymptotic unbiasedness and asymptotic variance, are established. The optimal estimator, in the sense of minimizing the asymptotic variance, is also presented. The proposed class contains several known types of estimators, such as ratio and regression estimators, which are of practical application and are therefore derived. Assuming several populations, the proposed estimators are compared with the direct estimator via an empirical study. Results show that a gain in efficiency can be obtained.
机译:研究了与在两个阶段中每个阶段都采用任意采样设计的双采样中分位数估计有关的实际问题。实际上,该方案通常用于官方调查,其中当调查处理诸如收入或支出之类的变量时,通常需要进行分位数估计。提出了一类分位数的估计量,并建立了一些重要的性质,例如渐近无偏性和渐近​​方差。在最小化渐近方差的意义上,还提供了最佳估计量。提议的类包含几种已知类型的估计量,例如比率估计量和回归估计量,它们是实际应用的,因此可以得出。假设有多个总体,则通过经验研究将建议的估计量与直接估计量进行比较。结果表明可以获得效率的提高。

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