广义西格玛量子函数

IF 2.3 3区社会学 Q1 AREA STUDIES

China Information Pub Date : 2024-01-01 Epub Date: 2022-02-28 DOI:10.1080/03610918.2022.2032161

Alan D Hutson

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引用次数: 0

摘要

在本论文中，我们介绍了一种基于新定义的广义期望值函数的新的平滑非参数量化函数估计器，称为西格玛量化函数估计器。我们还介绍了一种混合量化函数估计器，它结合了经典核量化函数估计器和我们新的广义西格玛量化函数估计器的最佳特性。广义 sigmoidal 量化函数可以估计超出数据范围的量化值，这对于样本量较小的某些应用非常重要。为了改进标准自举平滑重采样方法，我们对这一外推特性进行了说明。

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The generalized sigmoidal quantile function.

In this note we introduce a new smooth nonparametric quantile function estimator based on a newly defined generalized expectile function and termed the sigmoidal quantile function estimator. We also introduce a hybrid quantile function estimator, which combines the optimal properties of the classic kernel quantile function estimator with our new generalized sigmoidal quantile function estimator. The generalized sigmoidal quantile function can estimate quantiles beyond the range of the data, which is important for certain applications given smaller sample sizes. This property of extrapolation is illustrated in order to improve standard bootstrap smoothing resampling methods.

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来源期刊

China Information AREA STUDIES-

CiteScore

3.50

自引率

4.80%

发文量

期刊介绍： China Information presents timely and in-depth analyses of major developments in contemporary China and overseas Chinese communities in the areas of politics, economics, law, ecology, culture, and society, including literature and the arts. China Information pays special attention to views and areas that do not receive sufficient attention in the mainstream discourse on contemporary China. It encourages discussion and debate between different academic traditions, offers a platform to express controversial and dissenting opinions, and promotes research that is historically sensitive and contemporarily relevant.