{"title":"A New Hyperbolic Tangent Family of Distributions: Properties and Applications","authors":"Shahid Mohammad, Isabel Mendoza","doi":"10.1007/s40745-024-00516-5","DOIUrl":null,"url":null,"abstract":"<div><p>This paper introduces a new family of distributions called the hyperbolic tangent (HT) family. The cumulative distribution function of this model is defined using the standard hyperbolic tangent function. The fundamental properties of the distribution are thoroughly examined and presented. Additionally, an inverse exponential distribution is employed as a sub-model within the HT family, and its properties are also derived. The parameters of the HT family are estimated using the maximum likelihood method, and the performance of these estimators is assessed using a simulation approach. To demonstrate the significance and flexibility of the newly introduced family of distributions, two real data sets are utilized. These data sets serve as practical examples that showcase the applicability and usefulness of the HT family in real-world scenarios. By introducing the HT family, exploring its properties, employing the maximum likelihood estimation, and conducting simulations and real data analyses, this paper contributes to the advancement of statistical modeling and distribution theory.</p></div>","PeriodicalId":36280,"journal":{"name":"Annals of Data Science","volume":"12 2","pages":"457 - 480"},"PeriodicalIF":0.0000,"publicationDate":"2024-02-15","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/s40745-024-00516-5","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Decision Sciences","Score":null,"Total":0}
引用次数: 0
Abstract
This paper introduces a new family of distributions called the hyperbolic tangent (HT) family. The cumulative distribution function of this model is defined using the standard hyperbolic tangent function. The fundamental properties of the distribution are thoroughly examined and presented. Additionally, an inverse exponential distribution is employed as a sub-model within the HT family, and its properties are also derived. The parameters of the HT family are estimated using the maximum likelihood method, and the performance of these estimators is assessed using a simulation approach. To demonstrate the significance and flexibility of the newly introduced family of distributions, two real data sets are utilized. These data sets serve as practical examples that showcase the applicability and usefulness of the HT family in real-world scenarios. By introducing the HT family, exploring its properties, employing the maximum likelihood estimation, and conducting simulations and real data analyses, this paper contributes to the advancement of statistical modeling and distribution theory.
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.