Niladri Chakraborty, N. Balakrishnan, M. Finkelstein
{"title":"On precedence tests with double sampling","authors":"Niladri Chakraborty, N. Balakrishnan, M. Finkelstein","doi":"10.1080/02331888.2023.2203491","DOIUrl":null,"url":null,"abstract":"A new double sampling-based precedence and weighted precedence tests are introduced and analysed. The joint distributions of two precedence and weighted precedence statistics are obtained under the double-sampling framework. Subsequently, the closed-form expressions for the rejection probabilities are derived under the null hypothesis and the Lehmann alternative. The corresponding power comparison is carried out against the Lehmann alternative and the location-scale alternative through Monte-Carlo simulations. Finally, a couple of detailed illustrative examples are presented.","PeriodicalId":54358,"journal":{"name":"Statistics","volume":"48 1","pages":"554 - 576"},"PeriodicalIF":1.2000,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Statistics","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1080/02331888.2023.2203491","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
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Abstract
A new double sampling-based precedence and weighted precedence tests are introduced and analysed. The joint distributions of two precedence and weighted precedence statistics are obtained under the double-sampling framework. Subsequently, the closed-form expressions for the rejection probabilities are derived under the null hypothesis and the Lehmann alternative. The corresponding power comparison is carried out against the Lehmann alternative and the location-scale alternative through Monte-Carlo simulations. Finally, a couple of detailed illustrative examples are presented.
期刊介绍：
Statistics publishes papers developing and analysing new methods for any active field of statistics, motivated by real-life problems. Papers submitted for consideration should provide interesting and novel contributions to statistical theory and its applications with rigorous mathematical results and proofs. Moreover, numerical simulations and application to real data sets can improve the quality of papers, and should be included where appropriate. Statistics does not publish papers which represent mere application of existing procedures to case studies, and papers are required to contain methodological or theoretical innovation. Topics of interest include, for example, nonparametric statistics, time series, analysis of topological or functional data. Furthermore the journal also welcomes submissions in the field of theoretical econometrics and its links to mathematical statistics.
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