A recursive version of Grubbs' test for detecting multiple outliers in environmental and chemical data
A recursive version of Grubbs' test for detecting multiple outliers in environmental and chemical data
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DOI：
10.1016/j.clinbiochem.2010.04.071
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发表时间：
2010-08-01
影响因子：
2.8
通讯作者：
Jain, Ram B.
中科院分区：
文献类型：
--
作者：
Jain, Ram B.
目的：比较GRubbs离群点检测方法和递归极值学习偏差(ESD)离群点检测方法的性能。设计与方法：利用模拟数据对GRubbs离群点检测法和ESD离群点检测法的性能进行评价。结果：除样本中只有一个离群点外，ESD离群点检测法的检测能力均高于GRubbs离群点检测法。结论：ESD递归检测法是检测环境和化学数据中多个离群点的首选方法。(C)2010年加拿大临床化学家协会。爱思唯尔公司出版，版权所有。
Objective: To compare the performance of Grubbs outlier detection procedure with recursive Extreme Studentized Deviate (ESD) outlier detection procedure.Design and methods: Using simulated data, the powers of Grubbs' and ESD procedures were evaluated.Results: Except when the sample contained exactly one outlier, the power of ESD procedure was higher than that of Grubbs' procedure.Conclusion: The ESD recursive procedure is the procedure of choice to detect multiple Outliers in environmental and chemical data. (C) 2010 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.