左截尾样本下幂律分布拟合的Anderson-Darling检验
The Anderson-Darling test of fit for the power law distribution from left censored samples
摘要：
本文给出了幂律分布参数估计的左删失样本下基于Anderson-Darling统计量的极大似然估计和拟合检验。给出了A^2统计量的极大似然估计量的表达式和渐近百分点表。该技术是说明数据从道琼斯工业平均指数，一个例子，在经济物理学，金融，物理学，生物学，并在一般情况下，在其他相关的科学，如复杂性科学的理论和实践的重要性。
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
