检验方差齐性的精确p值新方法

IF 0.7 Q3 STATISTICS & PROBABILITY Statistical Theory and Related Fields Pub Date : 2021-04-22 DOI:10.1080/24754269.2021.1907519
Juan Wang, Xinmin Li, Huasu Liang
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引用次数: 1

摘要

为了检验方差的同质性,人们提出了各种基于似然比的检验,如Bartlett检验。这些检验的零分布一般是渐近或近似地推导出来的。我们重新研究了限制性最大似然比(RELR)统计量,并提出了一种蒙特卡罗算法来计算其精确的零分布,从而计算其p值。它比大多数现有方法更容易实现。仿真研究表明,该算法在I型误差和功率方面也优于同类算法。我们分析一个环境数据集来举例说明。
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A new exact p-value approach for testing variance homogeneity
To test variance homogeneity, various likelihood-ratio based tests such as the Bartlett's test have been proposed. The null distributions of these tests were generally derived asymptotically or approximately. We re-examine the restrictive maximum likelihood ratio (RELR) statistic, and suggest a Monte Carlo algorithm to compute its exact null distribution, and so its p-value. It is much easier to implement than most existing methods. Simulation studies indicate that the proposed procedure is also superior to its competitors in terms of type I error and powers. We analyse an environmental dataset for an illustration.
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来源期刊
CiteScore
0.90
自引率
20.00%
发文量
21
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