{"title":"对数对称分布的杰克刀经验似然比检验","authors":"Ganesh Vishnu Avhad, Ananya Lahiri","doi":"10.1016/j.spl.2025.110394","DOIUrl":null,"url":null,"abstract":"<div><div>A nonparametric test for assessing log-symmetric distributions is proposed, including the jackknife empirical likelihood and adjusted jackknife empirical likelihood ratio tests. The asymptotic distribution of the test statistic has been derived as well. A comprehensive Monte Carlo simulation study shows that the proposed tests exhibit good power against various alternative distributions. Additionally, the method is demonstrated using two real data sets to highlight their practical applicability.</div></div>","PeriodicalId":49475,"journal":{"name":"Statistics & Probability Letters","volume":"222 ","pages":"Article 110394"},"PeriodicalIF":0.9000,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A jackknife empirical likelihood ratio test for log-symmetric distributions\",\"authors\":\"Ganesh Vishnu Avhad, Ananya Lahiri\",\"doi\":\"10.1016/j.spl.2025.110394\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>A nonparametric test for assessing log-symmetric distributions is proposed, including the jackknife empirical likelihood and adjusted jackknife empirical likelihood ratio tests. The asymptotic distribution of the test statistic has been derived as well. A comprehensive Monte Carlo simulation study shows that the proposed tests exhibit good power against various alternative distributions. Additionally, the method is demonstrated using two real data sets to highlight their practical applicability.</div></div>\",\"PeriodicalId\":49475,\"journal\":{\"name\":\"Statistics & Probability Letters\",\"volume\":\"222 \",\"pages\":\"Article 110394\"},\"PeriodicalIF\":0.9000,\"publicationDate\":\"2025-02-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Statistics & Probability Letters\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0167715225000392\",\"RegionNum\":4,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"STATISTICS & PROBABILITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Statistics & Probability Letters","FirstCategoryId":"100","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0167715225000392","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
A jackknife empirical likelihood ratio test for log-symmetric distributions
A nonparametric test for assessing log-symmetric distributions is proposed, including the jackknife empirical likelihood and adjusted jackknife empirical likelihood ratio tests. The asymptotic distribution of the test statistic has been derived as well. A comprehensive Monte Carlo simulation study shows that the proposed tests exhibit good power against various alternative distributions. Additionally, the method is demonstrated using two real data sets to highlight their practical applicability.
期刊介绍:
Statistics & Probability Letters adopts a novel and highly innovative approach to the publication of research findings in statistics and probability. It features concise articles, rapid publication and broad coverage of the statistics and probability literature.
Statistics & Probability Letters is a refereed journal. Articles will be limited to six journal pages (13 double-space typed pages) including references and figures. Apart from the six-page limitation, originality, quality and clarity will be the criteria for choosing the material to be published in Statistics & Probability Letters. Every attempt will be made to provide the first review of a submitted manuscript within three months of submission.
The proliferation of literature and long publication delays have made it difficult for researchers and practitioners to keep up with new developments outside of, or even within, their specialization. The aim of Statistics & Probability Letters is to help to alleviate this problem. Concise communications (letters) allow readers to quickly and easily digest large amounts of material and to stay up-to-date with developments in all areas of statistics and probability.
The mainstream of Letters will focus on new statistical methods, theoretical results, and innovative applications of statistics and probability to other scientific disciplines. Key results and central ideas must be presented in a clear and concise manner. These results may be part of a larger study that the author will submit at a later time as a full length paper to SPL or to another journal. Theory and methodology may be published with proofs omitted, or only sketched, but only if sufficient support material is provided so that the findings can be verified. Empirical and computational results that are of significant value will be published.