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A new class of exponential regression cum ratio estimator in two phase sampling

机译：两阶段采样中的一类新的指数回归暨比率估计器

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The use of auxiliary information improves the precision of estimators of the population mean. If auxiliary information is available then ration and regression are used in many cases. Many studies have proposed various ratios and regression methods by using general linear transformation of the auxiliary variable. However the knowledge on the population mean of the auxiliary variable is not available. For such a situation most suitable is a the two phase sampling. Two phase sampling is used when data acquisition is costly but data collection of correlated variables is less expensive. In the first phase, a reliable estimate of the unknown parameters is derived. This is carried out to collect the average value of some characteristic such as the amount spends on food by a family. If a second characteristic is correlated with the first, then this parameter can be generated by a less expensive survey. Various ratio cum regression estimators are suggested by various authors for this purpose. This article proposes a class of exponential regression cum ratio estimator and is compared with other estimators. It is found that the proposed estimator is found to be more efficient than others under certain conditions. (20 refs.)
机译：辅助信息的使用提高了总体均值估算器的精度。如果可获得辅助信息，则在许多情况下会使用定量和回归。通过使用辅助变量的一般线性变换，许多研究提出了各种比率和回归方法。但是，尚无关于辅助变量的总体平均值的知识。对于这种情况，最合适的是两阶段采样。当数据获取成本高昂但相关变量的数据收集成本较低时，使用两阶段采样。在第一阶段，得出未知参数的可靠估计。这样做是为了收集某些特征的平均值，例如家庭在食物上的花费。如果第二个特征与第一个特征相关，则可以通过较便宜的调查来生成此参数。为此，各种作者提出了各种比率和回归估计量。本文提出了一类指数回归暨比率估计器，并与其他估计器进行了比较。发现在某些条件下，所提出的估计器比其他估计器更有效。 （20篇）

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