{"title":"变换的移位林德利分布:特征、经典和贝叶斯估计及其应用","authors":"A. Chakraborty, S. Rana, S. I. Maiti","doi":"10.1007/s40745-024-00562-z","DOIUrl":null,"url":null,"abstract":"<div><p>In this article, we propose the quadratic rank transmutation map approach on shifted Lindley distribution to improve the existing distribution further. An additional skewness parameter <span>\\(\\lambda \\)</span> is incorporated to transmute the distribution. The distribution, hence introduced, is called the Transmuted Shifted Lindley distribution. We provide a comprehensive description of this distribution’s statistical properties and its reliability behavior. The heat maps on the associated parameters are presented. In the estimation section, both maximum likelihood and Bayesian estimation of parameters are discussed. A detailed simulation study is performed. Finally, a real data application illustrates the performance of fitting to the proposed distribution.</p></div>","PeriodicalId":36280,"journal":{"name":"Annals of Data Science","volume":"12 4","pages":"1237 - 1264"},"PeriodicalIF":0.0000,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Transmuted Shifted Lindley Distribution: Characterizations, Classical and Bayesian Estimation with Applications\",\"authors\":\"A. Chakraborty, S. Rana, S. I. Maiti\",\"doi\":\"10.1007/s40745-024-00562-z\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>In this article, we propose the quadratic rank transmutation map approach on shifted Lindley distribution to improve the existing distribution further. An additional skewness parameter <span>\\\\(\\\\lambda \\\\)</span> is incorporated to transmute the distribution. The distribution, hence introduced, is called the Transmuted Shifted Lindley distribution. We provide a comprehensive description of this distribution’s statistical properties and its reliability behavior. The heat maps on the associated parameters are presented. In the estimation section, both maximum likelihood and Bayesian estimation of parameters are discussed. A detailed simulation study is performed. Finally, a real data application illustrates the performance of fitting to the proposed distribution.</p></div>\",\"PeriodicalId\":36280,\"journal\":{\"name\":\"Annals of Data Science\",\"volume\":\"12 4\",\"pages\":\"1237 - 1264\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-07-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Annals of Data Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s40745-024-00562-z\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Decision Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annals of Data Science","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.1007/s40745-024-00562-z","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Decision Sciences","Score":null,"Total":0}
Transmuted Shifted Lindley Distribution: Characterizations, Classical and Bayesian Estimation with Applications
In this article, we propose the quadratic rank transmutation map approach on shifted Lindley distribution to improve the existing distribution further. An additional skewness parameter \(\lambda \) is incorporated to transmute the distribution. The distribution, hence introduced, is called the Transmuted Shifted Lindley distribution. We provide a comprehensive description of this distribution’s statistical properties and its reliability behavior. The heat maps on the associated parameters are presented. In the estimation section, both maximum likelihood and Bayesian estimation of parameters are discussed. A detailed simulation study is performed. Finally, a real data application illustrates the performance of fitting to the proposed distribution.
期刊介绍:
Annals of Data Science (ADS) publishes cutting-edge research findings, experimental results and case studies of data science. Although Data Science is regarded as an interdisciplinary field of using mathematics, statistics, databases, data mining, high-performance computing, knowledge management and virtualization to discover knowledge from Big Data, it should have its own scientific contents, such as axioms, laws and rules, which are fundamentally important for experts in different fields to explore their own interests from Big Data. ADS encourages contributors to address such challenging problems at this exchange platform. At present, how to discover knowledge from heterogeneous data under Big Data environment needs to be addressed. ADS is a series of volumes edited by either the editorial office or guest editors. Guest editors will be responsible for call-for-papers and the review process for high-quality contributions in their volumes.