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A short note on quantile and expectile estimation in unequal probability samples

机译:关于不等概率样本中的分位数和预期估计的简短说明

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摘要

The estimation of quantiles is an important topic not only in the regression framework, but also in sampling theory. A natural alternative or addition to quantiles are expectiles. Expectiles as a generalization of the mean have become popular during the last years as they not only give a more detailed picture of the data than the ordinary mean, but also can serve as a basis to calculate quantiles by using their close relationship. We show, how to estimate expectiles under sampling with unequal probabilities and how expectiles can be used to estimate the distribution function. The resulting fitted distribution function estimator can be inverted leading to quantile estimates. We run a simulation study to investigate and compare the efficiency of the expectile based estimator.
机译:分位数的估计不仅在回归框架中,而且在抽样理论中都是重要的话题。分位数的自然替代品或附加物是分位数。在过去的几年中,作为平均值的一般化的期望值已经流行起来,因为它们不仅可以提供比普通平均值更详细的数据图,而且可以作为使用它们的紧密关系来计算分位数的基础。我们展示了如何在不等概率的采样下估计预期种群,以及如何将预期种群用于估计分布函数。所得的拟合分布函数估计量可以反转,从而导致分位数估计。我们进行了一项仿真研究,以调查和比较基于期望值的估算器的效率。

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