摘要翻译：
本文应用一种称为递增重排的正则化过程，单调化Edgeworth展开式和Cornish-Fisher展开式以及任何其他相关的分布近似和样本统计量的分位数函数。除了满足分布和分位数函数所要求的逻辑单调性外，该方法对样本均值的分布和分位数函数的逼近比原来的Edgeworth-Cornish-Fisher展开式要好得多。
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英文标题：
《Rearranging Edgeworth-Cornish-Fisher Expansions》
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作者：
Victor Chernozhukov, Ivan Fernandez-Val, Alfred Galichon
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最新提交年份：
2013
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分类信息：

一级分类：Statistics        统计学
二级分类：Methodology        方法论
分类描述：Design, Surveys, Model Selection, Multiple Testing, Multivariate Methods, Signal and Image Processing, Time Series, Smoothing, Spatial Statistics, Survival Analysis, Nonparametric and Semiparametric Methods
设计，调查，模型选择，多重检验，多元方法，信号和图像处理，时间序列，平滑，空间统计，生存分析，非参数和半参数方法
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一级分类：Economics        经济学
二级分类：Econometrics        计量经济学
分类描述：Econometric Theory, Micro-Econometrics, Macro-Econometrics, Empirical Content of Economic Relations discovered via New Methods, Methodological Aspects of the Application of Statistical Inference to Economic Data.
计量经济学理论，微观计量经济学，宏观计量经济学，通过新方法发现的经济关系的实证内容，统计推论应用于经济数据的方法论方面。
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英文摘要：
  This paper applies a regularization procedure called increasing rearrangement to monotonize Edgeworth and Cornish-Fisher expansions and any other related approximations of distribution and quantile functions of sample statistics. Besides satisfying the logical monotonicity, required of distribution and quantile functions, the procedure often delivers strikingly better approximations to the distribution and quantile functions of the sample mean than the original Edgeworth-Cornish-Fisher expansions.
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PDF链接：
https://arxiv.org/pdf/708.1627