摘要翻译：
针对幂律分布的情况，给出了左截尾样本参数估计的极大似然估计和基于Anderson-Darling统计量的拟合检验。给出了A^2统计量的极大似然估计表达式和渐近百分点表。道琼斯工业平均指数是一个在经济物理学、金融学、物理学、生物学以及其他相关科学（如复杂性科学）中具有高度理论和实际重要性的例子。
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英文标题：
《The Anderson-Darling test of fit for the power law distribution from
  left censored samples》
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作者：
H.F. Coronel-Brizio (1), A.R. Hernandez-Montoya (1) ((1) Facultad de
  Fisica e Inteligencia Artificial, Departamento de Inteligencia Artificial,
  Universidad Veracruzana, Mexico)
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最新提交年份：
2010
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分类信息：

一级分类：Physics        物理学
二级分类：Data Analysis, Statistics and Probability        数据分析、统计与概率
分类描述：Methods, software and hardware for physics data analysis: data processing and storage; measurement methodology; statistical and mathematical aspects such as parametrization and uncertainties.
物理数据分析的方法、软硬件：数据处理与存储；测量方法；统计和数学方面，如参数化和不确定性。
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一级分类：Quantitative Finance        数量金融学
二级分类：Statistical Finance        统计金融
分类描述：Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
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英文摘要：
  Maximum likelihood estimation and a test of fit based on the Anderson-Darling statistic is presented for the case of the power law distribution when the parameters are estimated from a left-censored sample. Expressions for the maximum likelihood estimators and tables of asymptotic percentage points for the A^2 statistic are given. The technique is illustrated for data from the Dow Jones Industrial Average index, an example of high theoretical and practical importance in Econophysics, Finance, Physics, Biology and, in general, in other related Sciences such as Complexity Sciences.
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PDF链接：
https://arxiv.org/pdf/1004.0417