Testing powers of the ratio of variances of two normal populations with a common mean

IF 1.1 4区 数学 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Pravash Jena, Manas Ranjan Tripathy
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引用次数: 0

Abstract

AbstractThis article addresses the problem of hypothesis testing about the powers of the ratio of variances of two normal populations with a common mean. Different test procedures are proposed, such as the likelihood ratio test, the standardized likelihood ratio test, the parametric bootstrap likelihood ratio test, the computational approach test and its modification. Further, several generalized p-value approach test procedures are derived using some of the existing common mean estimators. The performances of all the suggested test methods are compared numerically in terms of their size values and power functions. In light of our simulation findings, we provide a few suggestions for utilizing the proposed test methods. Finally, we analyse real-life data to show the potential application of the proposed model.Keywords: Bootstrap samplescommon meangeneralized p-valueplug-in estimatorsratio of variancespower functionsimulation studysize value2010 AMS Subject Classifications: 62F0362F0562F1065C05 AcknowledgmentsThe authors would like to sincerely thank the two anonymous reviewers, whose constructive and thoughtful comments on the earlier version of the manuscript led to greater improvements in the manuscript's content.Disclosure statementThe authors declare that there are no relevant financial or non-financial competing interests to report for this work.
具有共同均值的两个正态总体方差之比的检验能力
摘要本文讨论了具有共同均值的两个正态总体方差之比幂的假设检验问题。提出了不同的检验方法,如似然比检验、标准化似然比检验、参数自举似然比检验、计算方法检验及其修正。此外,利用一些现有的通用均值估计器,推导了几种广义p值方法检验程序。从尺寸值和幂函数的角度对所有测试方法的性能进行了数值比较。根据我们的模拟结果,我们提供了一些建议,利用提出的测试方法。最后,我们分析了实际数据,以显示所提出模型的潜在应用。关键词:Bootstrap样本共同均值广义p值插件估计方差比幂函数模拟研究大小值2010 AMS主题分类:62F0362F0562F1065C05致谢作者衷心感谢两位匿名审稿人,他们对早期版本手稿的建设性和周到的意见使手稿的内容得到了更大的改进。作者声明,本研究没有相关的财务或非财务竞争利益。
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来源期刊
Journal of Statistical Computation and Simulation
Journal of Statistical Computation and Simulation 数学-计算机:跨学科应用
CiteScore
2.30
自引率
8.30%
发文量
156
审稿时长
4-8 weeks
期刊介绍: Journal of Statistical Computation and Simulation ( JSCS ) publishes significant and original work in areas of statistics which are related to or dependent upon the computer. Fields covered include computer algorithms related to probability or statistics, studies in statistical inference by means of simulation techniques, and implementation of interactive statistical systems. JSCS does not consider applications of statistics to other fields, except as illustrations of the use of the original statistics presented. Accepted papers should ideally appeal to a wide audience of statisticians and provoke real applications of theoretical constructions.
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