{"title":"FGM generated archimedean copulas with concave multiplicative generators","authors":"N. Doodman, M. Amini, H. Jabbari, A. Dolati","doi":"10.22111/IJFS.2021.5911","DOIUrl":null,"url":null,"abstract":"The Farlie-Gumble-Morgenstren (FGM) family and archimedean family are the most popular parametric families of copulas. In the present paper, we propose an extension of archimedean copulas with concave multiplicative generators in the style of FGM family. In particular, our method allows the modelling of higher positive dependence than the other FGM extensions in the literature. The construction and characteristics of the proposed model along with some examples of parametric subfamilies are provided. A numerical study is used to illustrate the methodology.","PeriodicalId":54920,"journal":{"name":"Iranian Journal of Fuzzy Systems","volume":"115 1","pages":"15-29"},"PeriodicalIF":1.9000,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Iranian Journal of Fuzzy Systems","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.22111/IJFS.2021.5911","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICS","Score":null,"Total":0}
引用次数: 0
Abstract
The Farlie-Gumble-Morgenstren (FGM) family and archimedean family are the most popular parametric families of copulas. In the present paper, we propose an extension of archimedean copulas with concave multiplicative generators in the style of FGM family. In particular, our method allows the modelling of higher positive dependence than the other FGM extensions in the literature. The construction and characteristics of the proposed model along with some examples of parametric subfamilies are provided. A numerical study is used to illustrate the methodology.
期刊介绍:
The two-monthly Iranian Journal of Fuzzy Systems (IJFS) aims to provide an international forum for refereed original research works in the theory and applications of fuzzy sets and systems in the areas of foundations, pure mathematics, artificial intelligence, control, robotics, data analysis, data mining, decision making, finance and management, information systems, operations research, pattern recognition and image processing, soft computing and uncertainty modeling.
Manuscripts submitted to the IJFS must be original unpublished work and should not be in consideration for publication elsewhere.