用成对观察对均匀随机排序的检验

IF 1.5 2区数学 Q2 STATISTICS & PROBABILITY

Bernoulli Pub Date : 2021-11-01 DOI:10.3150/21-BEJ1322

Dewei Wang, Chuan-Fa Tang

{"title":"用成对观察对均匀随机排序的检验","authors":"Dewei Wang, Chuan-Fa Tang","doi":"10.3150/21-BEJ1322","DOIUrl":null,"url":null,"abstract":"This article develops a two-sample nonparametric goodness-of-fit (GOF) test for uniform stochastic ordering (USO) when observations are taken in pairs. We propose a data-driven critical value that controls the type I error and yields a consistent test. A simulation study illustrates the finite-sample performance of our test. All the proofs are included in the supplemental file.","PeriodicalId":55387,"journal":{"name":"Bernoulli","volume":"27 1","pages":"2556-2563"},"PeriodicalIF":1.5000,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Testing against uniform stochastic ordering with paired observations\",\"authors\":\"Dewei Wang, Chuan-Fa Tang\",\"doi\":\"10.3150/21-BEJ1322\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article develops a two-sample nonparametric goodness-of-fit (GOF) test for uniform stochastic ordering (USO) when observations are taken in pairs. We propose a data-driven critical value that controls the type I error and yields a consistent test. A simulation study illustrates the finite-sample performance of our test. All the proofs are included in the supplemental file.\",\"PeriodicalId\":55387,\"journal\":{\"name\":\"Bernoulli\",\"volume\":\"27 1\",\"pages\":\"2556-2563\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2021-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Bernoulli\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.3150/21-BEJ1322\",\"RegionNum\":2,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"STATISTICS & PROBABILITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bernoulli","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.3150/21-BEJ1322","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}

引用次数: 2

摘要

本文发展了一种双样本非参数拟合优度(GOF)检验，用于一致随机排序(USO)的成对观测。我们提出一个数据驱动的临界值来控制类型I错误并产生一致的测试。仿真研究证明了我们的测试的有限样本性能。所有的校样都包含在补充文件中。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Testing against uniform stochastic ordering with paired observations

This article develops a two-sample nonparametric goodness-of-fit (GOF) test for uniform stochastic ordering (USO) when observations are taken in pairs. We propose a data-driven critical value that controls the type I error and yields a consistent test. A simulation study illustrates the finite-sample performance of our test. All the proofs are included in the supplemental file.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Bernoulli 数学-统计学与概率论

CiteScore

3.40

自引率

0.00%

发文量

116

审稿时长

6-12 weeks

期刊介绍： BERNOULLI is the journal of the Bernoulli Society for Mathematical Statistics and Probability, issued four times per year. The journal provides a comprehensive account of important developments in the fields of statistics and probability, offering an international forum for both theoretical and applied work. BERNOULLI will publish: Papers containing original and significant research contributions: with background, mathematical derivation and discussion of the results in suitable detail and, where appropriate, with discussion of interesting applications in relation to the methodology proposed. Papers of the following two types will also be considered for publication, provided they are judged to enhance the dissemination of research: Review papers which provide an integrated critical survey of some area of probability and statistics and discuss important recent developments. Scholarly written papers on some historical significant aspect of statistics and probability.