{"title":"Copula modeling from Abe Sklar to the present day","authors":"Christian Genest , Ostap Okhrin , Taras Bodnar","doi":"10.1016/j.jmva.2023.105278","DOIUrl":null,"url":null,"abstract":"<div><p>This paper provides a structured overview of the contents of the Special Issue of the <span><em>Journal of </em><em>Multivariate Analysis</em></span> on “Copula modeling from Abe Sklar to the present day,” along with a brief history of the development of the field.</p></div>","PeriodicalId":16431,"journal":{"name":"Journal of Multivariate Analysis","volume":"201 ","pages":"Article 105278"},"PeriodicalIF":1.4000,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Multivariate Analysis","FirstCategoryId":"100","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0047259X23001240","RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
引用次数: 0
Abstract
This paper provides a structured overview of the contents of the Special Issue of the Journal of Multivariate Analysis on “Copula modeling from Abe Sklar to the present day,” along with a brief history of the development of the field.
期刊介绍:
Founded in 1971, the Journal of Multivariate Analysis (JMVA) is the central venue for the publication of new, relevant methodology and particularly innovative applications pertaining to the analysis and interpretation of multidimensional data.
The journal welcomes contributions to all aspects of multivariate data analysis and modeling, including cluster analysis, discriminant analysis, factor analysis, and multidimensional continuous or discrete distribution theory. Topics of current interest include, but are not limited to, inferential aspects of
Copula modeling
Functional data analysis
Graphical modeling
High-dimensional data analysis
Image analysis
Multivariate extreme-value theory
Sparse modeling
Spatial statistics.