New Families of Bivariate Copulas via Unit Lomax Distortion

This article studies a new family of bivariate copulas constructed using the unit-Lomax distortion derived from a transformation of the non-negative Lomax random variable into a variable whose support is the unit interval. Existing copulas play the role of the base copulas that are distorted into ne...

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Main Authors: Fadal Abdullah-A Aldhufairi, Ranadeera G.M. Samanthi, Jungsywan H. Sepanski
Format: Article
Language:English
Published: MDPI AG 2020-10-01
Series:Risks
Subjects:
Online Access:https://www.mdpi.com/2227-9091/8/4/106
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author Fadal Abdullah-A Aldhufairi
Ranadeera G.M. Samanthi
Jungsywan H. Sepanski
author_facet Fadal Abdullah-A Aldhufairi
Ranadeera G.M. Samanthi
Jungsywan H. Sepanski
author_sort Fadal Abdullah-A Aldhufairi
collection DOAJ
description This article studies a new family of bivariate copulas constructed using the unit-Lomax distortion derived from a transformation of the non-negative Lomax random variable into a variable whose support is the unit interval. Existing copulas play the role of the base copulas that are distorted into new families of copulas with additional parameters, allowing more flexibility and better fit to data. We present general forms for the new bivariate copula function and its conditional and density distributions. The properties of the new family of the unit-Lomax induced copulas, including the tail behaviors, limiting cases in parameters, Kendall’s tau, and concordance order, are investigated for cases when the base copulas are Archimedean, such as the Clayton, Gumbel, and Frank copulas. An empirical application of the proposed copula model is presented. The unit-Lomax distorted copula models outperform the base copulas.
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spelling doaj.art-909c55801f814de1913c41efc034739a2023-11-20T16:59:42ZengMDPI AGRisks2227-90912020-10-018410610.3390/risks8040106New Families of Bivariate Copulas via Unit Lomax DistortionFadal Abdullah-A Aldhufairi0Ranadeera G.M. Samanthi1Jungsywan H. Sepanski2Department of Statistics, Actuarial and Data Sciences, Central Michigan University, Mount Pleasant, MI 48859, USADepartment of Statistics, Actuarial and Data Sciences, Central Michigan University, Mount Pleasant, MI 48859, USADepartment of Statistics, Actuarial and Data Sciences, Central Michigan University, Mount Pleasant, MI 48859, USAThis article studies a new family of bivariate copulas constructed using the unit-Lomax distortion derived from a transformation of the non-negative Lomax random variable into a variable whose support is the unit interval. Existing copulas play the role of the base copulas that are distorted into new families of copulas with additional parameters, allowing more flexibility and better fit to data. We present general forms for the new bivariate copula function and its conditional and density distributions. The properties of the new family of the unit-Lomax induced copulas, including the tail behaviors, limiting cases in parameters, Kendall’s tau, and concordance order, are investigated for cases when the base copulas are Archimedean, such as the Clayton, Gumbel, and Frank copulas. An empirical application of the proposed copula model is presented. The unit-Lomax distorted copula models outperform the base copulas.https://www.mdpi.com/2227-9091/8/4/106Archimedean copuladistortionKendall’s taulomax distributiontail dependence
spellingShingle Fadal Abdullah-A Aldhufairi
Ranadeera G.M. Samanthi
Jungsywan H. Sepanski
New Families of Bivariate Copulas via Unit Lomax Distortion
Risks
Archimedean copula
distortion
Kendall’s tau
lomax distribution
tail dependence
title New Families of Bivariate Copulas via Unit Lomax Distortion
title_full New Families of Bivariate Copulas via Unit Lomax Distortion
title_fullStr New Families of Bivariate Copulas via Unit Lomax Distortion
title_full_unstemmed New Families of Bivariate Copulas via Unit Lomax Distortion
title_short New Families of Bivariate Copulas via Unit Lomax Distortion
title_sort new families of bivariate copulas via unit lomax distortion
topic Archimedean copula
distortion
Kendall’s tau
lomax distribution
tail dependence
url https://www.mdpi.com/2227-9091/8/4/106
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