{"title":"基于DUS变换的动力逆瑞利分布","authors":"M. I. Khan, A. Mustafa","doi":"10.28924/2291-8639-21-2023-61","DOIUrl":null,"url":null,"abstract":"This article reports an extension of powered inverse Rayleigh distribution via DUS transformation, named DUS-Powered Inverse Rayleigh (DUS-PIR) distribution. Some statistical properties of suggested distribution in particular, moments, mode, quantiles, order statistics, entropy, inequality measures and stress-strength parameter have been investigated extensively. To estimate the parameters, maximum likelihood estimation (MLE) is discussed. The model superiority is verified through two real datasets.","PeriodicalId":45204,"journal":{"name":"International Journal of Analysis and Applications","volume":" ","pages":""},"PeriodicalIF":0.7000,"publicationDate":"2023-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Powered Inverse Rayleigh Distribution Using DUS Transformation\",\"authors\":\"M. I. Khan, A. Mustafa\",\"doi\":\"10.28924/2291-8639-21-2023-61\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article reports an extension of powered inverse Rayleigh distribution via DUS transformation, named DUS-Powered Inverse Rayleigh (DUS-PIR) distribution. Some statistical properties of suggested distribution in particular, moments, mode, quantiles, order statistics, entropy, inequality measures and stress-strength parameter have been investigated extensively. To estimate the parameters, maximum likelihood estimation (MLE) is discussed. The model superiority is verified through two real datasets.\",\"PeriodicalId\":45204,\"journal\":{\"name\":\"International Journal of Analysis and Applications\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.7000,\"publicationDate\":\"2023-07-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Analysis and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.28924/2291-8639-21-2023-61\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MATHEMATICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Analysis and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.28924/2291-8639-21-2023-61","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATHEMATICS","Score":null,"Total":0}
Powered Inverse Rayleigh Distribution Using DUS Transformation
This article reports an extension of powered inverse Rayleigh distribution via DUS transformation, named DUS-Powered Inverse Rayleigh (DUS-PIR) distribution. Some statistical properties of suggested distribution in particular, moments, mode, quantiles, order statistics, entropy, inequality measures and stress-strength parameter have been investigated extensively. To estimate the parameters, maximum likelihood estimation (MLE) is discussed. The model superiority is verified through two real datasets.