{"title":"A data depth based nonparametric test of independence between two random vectors","authors":"Sakineh Dehghan, Mohammad Reza Faridrohani","doi":"10.1016/j.jmva.2024.105297","DOIUrl":null,"url":null,"abstract":"<div><p>A new family of depth-based test statistics is proposed for testing the hypothesis of independence between two random vectors. In the procedure to derive the asymptotic distribution of the tests under the null hypothesis, we do not require any symmetric assumption of the distribution functions. Furthermore, a conditional distribution-free property of the tests is shown. The asymptotic relative efficiency of the tests is discussed under the class of elliptically symmetric distribution. Asymptotic relative efficiencies along with Monte Carlo results suggest that the performance of the proposed class is comparable to the existing ones, and under some circumstances, it has higher power. Finally, we apply the tests to two real data sets and also discuss the robustness of our tests.</p></div>","PeriodicalId":1,"journal":{"name":"Accounts of Chemical Research","volume":null,"pages":null},"PeriodicalIF":16.4000,"publicationDate":"2024-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Accounts of Chemical Research","FirstCategoryId":"100","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0047259X24000046","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
A new family of depth-based test statistics is proposed for testing the hypothesis of independence between two random vectors. In the procedure to derive the asymptotic distribution of the tests under the null hypothesis, we do not require any symmetric assumption of the distribution functions. Furthermore, a conditional distribution-free property of the tests is shown. The asymptotic relative efficiency of the tests is discussed under the class of elliptically symmetric distribution. Asymptotic relative efficiencies along with Monte Carlo results suggest that the performance of the proposed class is comparable to the existing ones, and under some circumstances, it has higher power. Finally, we apply the tests to two real data sets and also discuss the robustness of our tests.
期刊介绍：
Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance.
Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.
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