{"title":"New copula families and mixing properties","authors":"Martial Longla","doi":"10.1007/s00362-024-01559-9","DOIUrl":null,"url":null,"abstract":"<p>We characterize absolutely continuous symmetric copulas with square integrable densities in this paper. This characterization is used to create new copula families, that are perturbations of the independence copula. The full study of mixing properties of Markov chains generated by these copula families is conducted. An extension that includes the Farlie–Gumbel–Morgenstern family of copulas is proposed. We propose some examples of copulas that generate non-mixing Markov chains, but whose convex combinations generate <span>\\(\\psi \\)</span>-mixing Markov chains. Some general results on <span>\\(\\psi \\)</span>-mixing are given. The Spearman’s correlation <span>\\(\\rho _S\\)</span> and Kendall’s <span>\\(\\tau \\)</span> are provided for the created copula families. Some general remarks are provided for <span>\\(\\rho _S\\)</span> and <span>\\(\\tau \\)</span>. A central limit theorem is provided for parameter estimators in one example. A simulation study is conducted to support derived asymptotic distributions for some examples.</p>","PeriodicalId":51166,"journal":{"name":"Statistical Papers","volume":"32 1","pages":""},"PeriodicalIF":1.2000,"publicationDate":"2024-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Statistical Papers","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1007/s00362-024-01559-9","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
We characterize absolutely continuous symmetric copulas with square integrable densities in this paper. This characterization is used to create new copula families, that are perturbations of the independence copula. The full study of mixing properties of Markov chains generated by these copula families is conducted. An extension that includes the Farlie–Gumbel–Morgenstern family of copulas is proposed. We propose some examples of copulas that generate non-mixing Markov chains, but whose convex combinations generate \(\psi \)-mixing Markov chains. Some general results on \(\psi \)-mixing are given. The Spearman’s correlation \(\rho _S\) and Kendall’s \(\tau \) are provided for the created copula families. Some general remarks are provided for \(\rho _S\) and \(\tau \). A central limit theorem is provided for parameter estimators in one example. A simulation study is conducted to support derived asymptotic distributions for some examples.
期刊介绍:
The journal Statistical Papers addresses itself to all persons and organizations that have to deal with statistical methods in their own field of work. It attempts to provide a forum for the presentation and critical assessment of statistical methods, in particular for the discussion of their methodological foundations as well as their potential applications. Methods that have broad applications will be preferred. However, special attention is given to those statistical methods which are relevant to the economic and social sciences. In addition to original research papers, readers will find survey articles, short notes, reports on statistical software, problem section, and book reviews.