{"title":"三次变形瑞利分布:理论与应用","authors":"M. Rahman","doi":"10.17713/ajs.v51i3.1280","DOIUrl":null,"url":null,"abstract":"In this paper, the Rayleigh distribution is generalized using the cubic transmuted (CT) family studied by Rahman et al. (in EJPAM, 12(3), 1106-1121, 2019) to propose a cubic transmuted Rayleigh distribution. An overall description is presented here for the distributional properties, parameter estimation, inference procedure, reliability behavior, and distribution of different order statistics. A real-life data set is used to demonstrate the applicability of the proposed distribution for modeling data.","PeriodicalId":51761,"journal":{"name":"Austrian Journal of Statistics","volume":"13 1","pages":""},"PeriodicalIF":0.6000,"publicationDate":"2022-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Cubic Transmuted Rayleigh Distribution: Theory and Application\",\"authors\":\"M. Rahman\",\"doi\":\"10.17713/ajs.v51i3.1280\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, the Rayleigh distribution is generalized using the cubic transmuted (CT) family studied by Rahman et al. (in EJPAM, 12(3), 1106-1121, 2019) to propose a cubic transmuted Rayleigh distribution. An overall description is presented here for the distributional properties, parameter estimation, inference procedure, reliability behavior, and distribution of different order statistics. A real-life data set is used to demonstrate the applicability of the proposed distribution for modeling data.\",\"PeriodicalId\":51761,\"journal\":{\"name\":\"Austrian Journal of Statistics\",\"volume\":\"13 1\",\"pages\":\"\"},\"PeriodicalIF\":0.6000,\"publicationDate\":\"2022-08-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Austrian Journal of Statistics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.17713/ajs.v51i3.1280\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"STATISTICS & PROBABILITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Austrian Journal of Statistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.17713/ajs.v51i3.1280","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
Cubic Transmuted Rayleigh Distribution: Theory and Application
In this paper, the Rayleigh distribution is generalized using the cubic transmuted (CT) family studied by Rahman et al. (in EJPAM, 12(3), 1106-1121, 2019) to propose a cubic transmuted Rayleigh distribution. An overall description is presented here for the distributional properties, parameter estimation, inference procedure, reliability behavior, and distribution of different order statistics. A real-life data set is used to demonstrate the applicability of the proposed distribution for modeling data.
期刊介绍:
The Austrian Journal of Statistics is an open-access journal (without any fees) with a long history and is published approximately quarterly by the Austrian Statistical Society. Its general objective is to promote and extend the use of statistical methods in all kind of theoretical and applied disciplines. The Austrian Journal of Statistics is indexed in many data bases, such as Scopus (by Elsevier), Web of Science - ESCI by Clarivate Analytics (formely Thompson & Reuters), DOAJ, Scimago, and many more. The current estimated impact factor (via Publish or Perish) is 0.775, see HERE, or even more indices HERE. Austrian Journal of Statistics ISNN number is 1026597X Original papers and review articles in English will be published in the Austrian Journal of Statistics if judged consistently with these general aims. All papers will be refereed. Special topics sections will appear from time to time. Each section will have as a theme a specialized area of statistical application, theory, or methodology. Technical notes or problems for considerations under Shorter Communications are also invited. A special section is reserved for book reviews.