A mixture of regular vines for multiple dependencies
type: Item
instance of: scholarly article
title: A mixture of regular vines for multiple dependencies
zbMATH Open document ID: 1468.62287
DOI: 10.1155/2021/5559518
author: Fadhah Amer Alanazi
published in: Journal of Probability and Statistics
publication date: 2021-07-02T00:00:00Z
review text: Summary: To uncover complex hidden dependency structures among variables, researchers have used a mixture of vine copula constructions. To date, these have been limited to a subclass of regular vine models, the so-called drawable vine, fitting only one type of bivariate copula for all variable pairs. However, the variation of complex hidden correlations from one pair of variables to another is more likely to be present in many real datasets. Single-type bivariate copulas are unable to deal with such a problem. In addition, the regular vine copula model is much more capable and flexible than its subclasses. Hence, to fully uncover and describe complex hidden dependency structures among variables and provide even further flexibility to the mixture of regular vine models, a mixture of regular vine models, with a mixed choice of bivariate copulas, is proposed in this paper. The model was applied to simulated and real data to illustrate its performance. The proposed model shows significant performance over the mixture of R-vine densities with a single copula family fitted to all pairs.
Mathematics Subject Classification ID: 62H05
Mathematics Subject Classification ID: 62P30
zbMATH DE Number: 7367192
zbMATH Keywords: mixture of vine copula constructions
zbMATH Keywords: glass data
Wikidata QID: Q114069969
describes a project that uses: CopulaModel
describes a project that uses: copula
describes a project that uses: R
describes a project that uses: JStatCom
describes a project that uses: VineCopula
describes a project that uses: nacopula
describes a project that uses: KEEL
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2021/5559518
OpenAlex ID: W3157247810
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description: scientific article; zbMATH DE number 7367192