{"title":"幂指数概率分布:统计推断与应用","authors":"","doi":"10.1016/j.aej.2024.07.038","DOIUrl":null,"url":null,"abstract":"<div><p>We introduce a generalized version of a unit distribution called power unit exponential probability distribution (PUEPrD) using the power transformation of the unit exponential probability distribution. Some statistical properties of the proposed distribution are derived. For some selected parameter cases, we have demonstrated that the hazard function of the proposed distribution can be shaped by increasing and bathtub curves. Twelve estimation methods such as maximum likelihood, Anderson–Darling, Cramer–von-Mises, maximum product spacings, least squares, weighted least squares, right tail Anderson Darling, left-tail Anderson Darling, minimum spacing absolute distance, minimum spacing absolute-log distance, Anderson Darling left-tail second order, Kolmogorov are used to estimate the parameters of the suggested distribution. A numerical simulation study is conducted to check the efficiency of the parameter estimates of the proposed model. With the help of some real-life data sets, the flexibility and usefulness of the PUEPrD are illustrated. As a result of two real data analyses, we observe that the fit of the proposed distribution to the data is superior to its competitors according to the examined criteria.</p></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":null,"pages":null},"PeriodicalIF":6.2000,"publicationDate":"2024-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1110016824007579/pdfft?md5=344508c0647201b094d0889021b0da42&pid=1-s2.0-S1110016824007579-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Power unit exponential probability distribution: Statistical inference and applications\",\"authors\":\"\",\"doi\":\"10.1016/j.aej.2024.07.038\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>We introduce a generalized version of a unit distribution called power unit exponential probability distribution (PUEPrD) using the power transformation of the unit exponential probability distribution. Some statistical properties of the proposed distribution are derived. For some selected parameter cases, we have demonstrated that the hazard function of the proposed distribution can be shaped by increasing and bathtub curves. Twelve estimation methods such as maximum likelihood, Anderson–Darling, Cramer–von-Mises, maximum product spacings, least squares, weighted least squares, right tail Anderson Darling, left-tail Anderson Darling, minimum spacing absolute distance, minimum spacing absolute-log distance, Anderson Darling left-tail second order, Kolmogorov are used to estimate the parameters of the suggested distribution. A numerical simulation study is conducted to check the efficiency of the parameter estimates of the proposed model. With the help of some real-life data sets, the flexibility and usefulness of the PUEPrD are illustrated. As a result of two real data analyses, we observe that the fit of the proposed distribution to the data is superior to its competitors according to the examined criteria.</p></div>\",\"PeriodicalId\":7484,\"journal\":{\"name\":\"alexandria engineering journal\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":6.2000,\"publicationDate\":\"2024-07-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S1110016824007579/pdfft?md5=344508c0647201b094d0889021b0da42&pid=1-s2.0-S1110016824007579-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"alexandria engineering journal\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1110016824007579\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"alexandria engineering journal","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1110016824007579","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
Power unit exponential probability distribution: Statistical inference and applications
We introduce a generalized version of a unit distribution called power unit exponential probability distribution (PUEPrD) using the power transformation of the unit exponential probability distribution. Some statistical properties of the proposed distribution are derived. For some selected parameter cases, we have demonstrated that the hazard function of the proposed distribution can be shaped by increasing and bathtub curves. Twelve estimation methods such as maximum likelihood, Anderson–Darling, Cramer–von-Mises, maximum product spacings, least squares, weighted least squares, right tail Anderson Darling, left-tail Anderson Darling, minimum spacing absolute distance, minimum spacing absolute-log distance, Anderson Darling left-tail second order, Kolmogorov are used to estimate the parameters of the suggested distribution. A numerical simulation study is conducted to check the efficiency of the parameter estimates of the proposed model. With the help of some real-life data sets, the flexibility and usefulness of the PUEPrD are illustrated. As a result of two real data analyses, we observe that the fit of the proposed distribution to the data is superior to its competitors according to the examined criteria.
期刊介绍:
Alexandria Engineering Journal is an international journal devoted to publishing high quality papers in the field of engineering and applied science. Alexandria Engineering Journal is cited in the Engineering Information Services (EIS) and the Chemical Abstracts (CA). The papers published in Alexandria Engineering Journal are grouped into five sections, according to the following classification:
• Mechanical, Production, Marine and Textile Engineering
• Electrical Engineering, Computer Science and Nuclear Engineering
• Civil and Architecture Engineering
• Chemical Engineering and Applied Sciences
• Environmental Engineering