{"title":"累积熵/外向性、基尼均值差与概率加权矩的关系","authors":"S. Kattumannil, E. Sreedevi, N. Balakrishnan","doi":"10.1017/s026996482200047x","DOIUrl":null,"url":null,"abstract":"\n In this work, we establish a connection between the cumulative residual entropy and the Gini mean difference (GMD). Some relationships between the extropy and the GMD, and the truncated GMD and dynamic versions of the cumulative past extropy are also established. We then show that several entropy and extropy measures discussed here can be brought into the framework of probability weighted moments, which would facilitate finding estimators of these measures.","PeriodicalId":54582,"journal":{"name":"Probability in the Engineering and Informational Sciences","volume":"86 1","pages":""},"PeriodicalIF":0.7000,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Relationships between cumulative entropy/extropy, Gini mean difference and probability weighted moments\",\"authors\":\"S. Kattumannil, E. Sreedevi, N. Balakrishnan\",\"doi\":\"10.1017/s026996482200047x\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n In this work, we establish a connection between the cumulative residual entropy and the Gini mean difference (GMD). Some relationships between the extropy and the GMD, and the truncated GMD and dynamic versions of the cumulative past extropy are also established. We then show that several entropy and extropy measures discussed here can be brought into the framework of probability weighted moments, which would facilitate finding estimators of these measures.\",\"PeriodicalId\":54582,\"journal\":{\"name\":\"Probability in the Engineering and Informational Sciences\",\"volume\":\"86 1\",\"pages\":\"\"},\"PeriodicalIF\":0.7000,\"publicationDate\":\"2022-08-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Probability in the Engineering and Informational Sciences\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1017/s026996482200047x\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENGINEERING, INDUSTRIAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Probability in the Engineering and Informational Sciences","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1017/s026996482200047x","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
Relationships between cumulative entropy/extropy, Gini mean difference and probability weighted moments
In this work, we establish a connection between the cumulative residual entropy and the Gini mean difference (GMD). Some relationships between the extropy and the GMD, and the truncated GMD and dynamic versions of the cumulative past extropy are also established. We then show that several entropy and extropy measures discussed here can be brought into the framework of probability weighted moments, which would facilitate finding estimators of these measures.
期刊介绍:
The primary focus of the journal is on stochastic modelling in the physical and engineering sciences, with particular emphasis on queueing theory, reliability theory, inventory theory, simulation, mathematical finance and probabilistic networks and graphs. Papers on analytic properties and related disciplines are also considered, as well as more general papers on applied and computational probability, if appropriate. Readers include academics working in statistics, operations research, computer science, engineering, management science and physical sciences as well as industrial practitioners engaged in telecommunications, computer science, financial engineering, operations research and management science.