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Characterization of pre-idempotent Copulas 前幂等copula的性质
Dependence Modeling Pub Date : 2023-01-01 DOI: 10.1515/demo-2023-0106
Wongtawan Chamnan, Songkiat Sumetkijakan
{"title":"Characterization of pre-idempotent Copulas","authors":"Wongtawan Chamnan, Songkiat Sumetkijakan","doi":"10.1515/demo-2023-0106","DOIUrl":"https://doi.org/10.1515/demo-2023-0106","url":null,"abstract":"Abstract Copulas <m:math xmlns:m=\"http://www.w3.org/1998/Math/MathML\"> <m:mi>C</m:mi> </m:math> C for which <m:math xmlns:m=\"http://www.w3.org/1998/Math/MathML\"> <m:msup> <m:mrow> <m:mrow> <m:mo stretchy=\"false\">(</m:mo> <m:mrow> <m:msup> <m:mrow> <m:mi>C</m:mi> </m:mrow> <m:mrow> <m:mi>t</m:mi> </m:mrow> </m:msup> <m:mi>C</m:mi> </m:mrow> <m:mo stretchy=\"false\">)</m:mo> </m:mrow> </m:mrow> <m:mrow> <m:mn>2</m:mn> </m:mrow> </m:msup> <m:mo>=</m:mo> <m:msup> <m:mrow> <m:mi>C</m:mi> </m:mrow> <m:mrow> <m:mi>t</m:mi> </m:mrow> </m:msup> <m:mi>C</m:mi> </m:math> {({C}^{t}C)}^{2}={C}^{t}C are called pre-idempotent copulas, of which well-studied examples are idempotent copulas and complete dependence copulas. As such, we shall work mainly with the topology induced by the modified Sobolev norm, with respect to which the class <m:math xmlns:m=\"http://www.w3.org/1998/Math/MathML\"> <m:mi class=\"MJX-tex-caligraphic\" mathvariant=\"script\">ℛ</m:mi> </m:math> {mathcal{ {mathcal R} }} of pre-idempotent copulas is closed and the class of factorizable copulas is a dense subset of <m:math xmlns:m=\"http://www.w3.org/1998/Math/MathML\"> <m:mi class=\"MJX-tex-caligraphic\" mathvariant=\"script\">ℛ</m:mi> </m:math> {mathcal{ {mathcal R} }} . Identifying copulas with Markov operators on <m:math xmlns:m=\"http://www.w3.org/1998/Math/MathML\"> <m:msup> <m:mrow> <m:mi>L</m:mi> </m:mrow> <m:mrow> <m:mn>2</m:mn> </m:mrow> </m:msup> </m:math> {L}^{2} , the one-to-one correspondence between pre-idempotent copulas and partial isometries is one of our main tools. In the same spirit as Darsow and Olsen’s work on idempotent copulas, we obtain an explicit characterization of pre-idempotent copulas, which is split into cases according to the atomicity of its associated <m:math xmlns:m=\"http://www.w3.org/1998/Math/MathML\"> <m:mi>σ</m:mi> </m:math> sigma -algebras, where the nonatomic case gives all factorizable copulas and the totally atomic case yields conjugates of ordinal sums of copies of the product copula.","PeriodicalId":43690,"journal":{"name":"Dependence Modeling","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135661990","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
When copulas and smoothing met: An interview with Irène Gijbels 当交配和平滑相遇:Irène Gijbels访谈
IF 0.7
Dependence Modeling Pub Date : 2023-01-01 DOI: 10.1515/demo-2022-0154
C. Genest, M. Scherer
{"title":"When copulas and smoothing met: An interview with Irène Gijbels","authors":"C. Genest, M. Scherer","doi":"10.1515/demo-2022-0154","DOIUrl":"https://doi.org/10.1515/demo-2022-0154","url":null,"abstract":"","PeriodicalId":43690,"journal":{"name":"Dependence Modeling","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49362457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Joint lifetime modeling with matrix distributions 基于矩阵分布的关节寿命建模
IF 0.7
Dependence Modeling Pub Date : 2023-01-01 DOI: 10.1515/demo-2022-0153
H. Albrecher, Martin Bladt, Alaric J. A. Müller
{"title":"Joint lifetime modeling with matrix distributions","authors":"H. Albrecher, Martin Bladt, Alaric J. A. Müller","doi":"10.1515/demo-2022-0153","DOIUrl":"https://doi.org/10.1515/demo-2022-0153","url":null,"abstract":"Abstract Acyclic phase-type (PH) distributions have been a popular tool in survival analysis, thanks to their natural interpretation in terms of aging toward its inevitable absorption. In this article, we consider an extension to the bivariate setting for the modeling of joint lifetimes. In contrast to previous models in the literature that were based on a separate estimation of the marginal behavior and the dependence structure through a copula, we propose a new time-inhomogeneous version of a multivariate PH (mIPH) class that leads to a model for joint lifetimes without that separation. We study properties of mIPH class members and provide an adapted estimation procedure that allows for right-censoring and covariate information. We show that initial distribution vectors in our construction can be tailored to reflect the dependence of the random variables and use multinomial regression to determine the influence of covariates on starting probabilities. Moreover, we highlight the flexibility and parsimony, in terms of needed phases, introduced by the time inhomogeneity. Numerical illustrations are given for the data set of joint lifetimes of Frees et al., where 10 phases turn out to be sufficient for a reasonable fitting performance. As a by-product, the proposed approach enables a natural causal interpretation of the association in the aging mechanism of joint lifetimes that goes beyond a statistical fit.","PeriodicalId":43690,"journal":{"name":"Dependence Modeling","volume":"11 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45079171","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Test of bivariate independence based on angular probability integral transform with emphasis on circular-circular and circular-linear data 基于角概率积分变换的二元独立性检验,重点是圆-圆和圆-线性数据
Dependence Modeling Pub Date : 2023-01-01 DOI: 10.1515/demo-2023-0103
Juan José Fernández-Durán, María Mercedes Gregorio-Domínguez
{"title":"Test of bivariate independence based on angular probability integral transform with emphasis on circular-circular and circular-linear data","authors":"Juan José Fernández-Durán, María Mercedes Gregorio-Domínguez","doi":"10.1515/demo-2023-0103","DOIUrl":"https://doi.org/10.1515/demo-2023-0103","url":null,"abstract":"Abstract The probability integral transform of a continuous random variable <m:math xmlns:m=\"http://www.w3.org/1998/Math/MathML\"> <m:mi>X</m:mi> </m:math> X with distribution function <m:math xmlns:m=\"http://www.w3.org/1998/Math/MathML\"> <m:msub> <m:mrow> <m:mi>F</m:mi> </m:mrow> <m:mrow> <m:mi>X</m:mi> </m:mrow> </m:msub> </m:math> {F}_{X} is a uniformly distributed random variable <m:math xmlns:m=\"http://www.w3.org/1998/Math/MathML\"> <m:mi>U</m:mi> <m:mo>=</m:mo> <m:msub> <m:mrow> <m:mi>F</m:mi> </m:mrow> <m:mrow> <m:mi>X</m:mi> </m:mrow> </m:msub> <m:mrow> <m:mo>(</m:mo> <m:mrow> <m:mi>X</m:mi> </m:mrow> <m:mo>)</m:mo> </m:mrow> </m:math> U={F}_{X}left(X) . We define the angular probability integral transform (APIT) as <m:math xmlns:m=\"http://www.w3.org/1998/Math/MathML\"> <m:msub> <m:mrow> <m:mi>θ</m:mi> </m:mrow> <m:mrow> <m:mi>U</m:mi> </m:mrow> </m:msub> <m:mo>=</m:mo> <m:mn>2</m:mn> <m:mi>π</m:mi> <m:mi>U</m:mi> <m:mo>=</m:mo> <m:mn>2</m:mn> <m:mi>π</m:mi> <m:msub> <m:mrow> <m:mi>F</m:mi> </m:mrow> <m:mrow> <m:mi>X</m:mi> </m:mrow> </m:msub> <m:mrow> <m:mo>(</m:mo> <m:mrow> <m:mi>X</m:mi> </m:mrow> <m:mo>)</m:mo> </m:mrow> </m:math> {theta }_{U}=2pi U=2pi {F}_{X}left(X) , which corresponds to a uniformly distributed angle on the unit circle. For circular (angular) random variables, the sum modulus 2 <m:math xmlns:m=\"http://www.w3.org/1998/Math/MathML\"> <m:mi>π</m:mi> </m:math> pi of absolutely continuous independent circular uniform random variables is a circular uniform random variable, that is, the circular uniform distribution is closed under summation modulus 2 <m:math xmlns:m=\"http://www.w3.org/1998/Math/MathML\"> <m:mi>π</m:mi> </m:math> pi , and it is a stable continuous distribution on the unit circle. If we consider the sum (difference) of the APITs of two random variables, <m:math xmlns:m=\"http://www.w3.org/1998/Math/MathML\"> <m:msub> <m:mrow> <m:mi>X</m:mi> </m:mrow> <m:mrow> <m:mn>1</m:mn> </m:mrow> </m:msub> </m:math> {X}_{1} and <m:math xmlns:m=\"http://www.w3.org/1998/Math/MathML\"> <m:msub> <m:mrow> <m:mi>X</m:mi> </m:mrow> <m:mrow> <m:mn>2</m:mn> </m:mrow> </m:msub> </m:math> {X}_{2} , and test for the circular uniformity of their sum (difference) modulus 2 <m:math xmlns:m=\"http://www.w3.org/1998/Math/MathML\"> <m:mi>π</m:mi> </m:math> pi , this is equivalent to test of independence of the original variables. In this study, we used a flexible family of nonnegative trigonometric sums (NNTS) circular distributions, which include the uniform circular distribution as a member of the family, to evaluate the power of the proposed independence test by generating samples from NNTS alternative distributions that could be at a closer proximity with respect to the circular uniform null distribution.","PeriodicalId":43690,"journal":{"name":"Dependence Modeling","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135059226","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Testing for explosive bubbles: a review 爆炸性气泡的测试:综述
Dependence Modeling Pub Date : 2023-01-01 DOI: 10.1515/demo-2022-0152
Anton Skrobotov
{"title":"Testing for explosive bubbles: a review","authors":"Anton Skrobotov","doi":"10.1515/demo-2022-0152","DOIUrl":"https://doi.org/10.1515/demo-2022-0152","url":null,"abstract":"Abstract This review discusses methods of testing for explosive bubbles in time series. A large number of recently developed testing methods under various assumptions about innovation of errors are covered. The review also considers the methods for dating explosive (bubble) regimes. Special attention is devoted to time-varying volatility in the errors. Moreover, the modelling of possible relationships between time series with explosive regimes is discussed.","PeriodicalId":43690,"journal":{"name":"Dependence Modeling","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135126904","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Functions operating on several multivariate distribution functions 作用于多个多元分布函数的函数
Dependence Modeling Pub Date : 2023-01-01 DOI: 10.1515/demo-2023-0104
Paul Ressel
{"title":"Functions operating on several multivariate distribution functions","authors":"Paul Ressel","doi":"10.1515/demo-2023-0104","DOIUrl":"https://doi.org/10.1515/demo-2023-0104","url":null,"abstract":"Abstract Functions <m:math xmlns:m=\"http://www.w3.org/1998/Math/MathML\"> <m:mi>f</m:mi> </m:math> f on <m:math xmlns:m=\"http://www.w3.org/1998/Math/MathML\"> <m:msup> <m:mrow> <m:mrow> <m:mo>[</m:mo> <m:mrow> <m:mn>0</m:mn> <m:mo>,</m:mo> <m:mn>1</m:mn> </m:mrow> <m:mo>]</m:mo> </m:mrow> </m:mrow> <m:mrow> <m:mi>m</m:mi> </m:mrow> </m:msup> </m:math> {left[0,1]}^{m} such that every composition <m:math xmlns:m=\"http://www.w3.org/1998/Math/MathML\"> <m:mi>f</m:mi> <m:mrow> <m:mo>∘</m:mo> </m:mrow> <m:mrow> <m:mo>(</m:mo> <m:mrow> <m:msub> <m:mrow> <m:mi>g</m:mi> </m:mrow> <m:mrow> <m:mn>1</m:mn> </m:mrow> </m:msub> <m:mo>,</m:mo> <m:mrow> <m:mo>…</m:mo> </m:mrow> <m:mo>,</m:mo> <m:msub> <m:mrow> <m:mi>g</m:mi> </m:mrow> <m:mrow> <m:mi>m</m:mi> </m:mrow> </m:msub> </m:mrow> <m:mo>)</m:mo> </m:mrow> </m:math> fcirc left({g}_{1},ldots ,{g}_{m}) with <m:math xmlns:m=\"http://www.w3.org/1998/Math/MathML\"> <m:mi>d</m:mi> </m:math> d -dimensional distribution functions <m:math xmlns:m=\"http://www.w3.org/1998/Math/MathML\"> <m:msub> <m:mrow> <m:mi>g</m:mi> </m:mrow> <m:mrow> <m:mn>1</m:mn> </m:mrow> </m:msub> <m:mo form=\"prefix\">,</m:mo> <m:mrow> <m:mo>…</m:mo> </m:mrow> <m:mo>,</m:mo> <m:msub> <m:mrow> <m:mi>g</m:mi> </m:mrow> <m:mrow> <m:mi>m</m:mi> </m:mrow> </m:msub> </m:math> {g}_{1},ldots ,{g}_{m} is again a distribution function, turn out to be characterized by a very natural monotonicity condition, which for <m:math xmlns:m=\"http://www.w3.org/1998/Math/MathML\"> <m:mi>d</m:mi> <m:mo>=</m:mo> <m:mn>2</m:mn> </m:math> d=2 means ultramodularity. For <m:math xmlns:m=\"http://www.w3.org/1998/Math/MathML\"> <m:mi>m</m:mi> <m:mo>=</m:mo> <m:mn>1</m:mn> </m:math> m=1 (and <m:math xmlns:m=\"http://www.w3.org/1998/Math/MathML\"> <m:mi>d</m:mi> <m:mo>=</m:mo> <m:mn>2</m:mn> </m:math> d=2 ), this is equivalent with increasing convexity.","PeriodicalId":43690,"journal":{"name":"Dependence Modeling","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135007458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A link between Kendall’s τ, the length measure and the surface of bivariate copulas, and a consequence to copulas with self-similar support 研究了肯德尔τ、长度度量和二元连簇表面之间的联系,以及对具有自相似支持的连簇的推论
Dependence Modeling Pub Date : 2023-01-01 DOI: 10.1515/demo-2023-0105
Juan Fernández Sánchez, Wolfgang Trutschnig
{"title":"A link between Kendall’s <i>τ</i>, the length measure and the surface of bivariate copulas, and a consequence to copulas with self-similar support","authors":"Juan Fernández Sánchez, Wolfgang Trutschnig","doi":"10.1515/demo-2023-0105","DOIUrl":"https://doi.org/10.1515/demo-2023-0105","url":null,"abstract":"Abstract Working with shuffles, we establish a close link between Kendall’s <m:math xmlns:m=\"http://www.w3.org/1998/Math/MathML\"> <m:mi>τ</m:mi> </m:math> tau , the so-called length measure, and the surface area of bivariate copulas and derive some consequences. While it is well known that Spearman’s <m:math xmlns:m=\"http://www.w3.org/1998/Math/MathML\"> <m:mi>ρ</m:mi> </m:math> rho of a bivariate copula <m:math xmlns:m=\"http://www.w3.org/1998/Math/MathML\"> <m:mi>A</m:mi> </m:math> A is a rescaled version of the volume of the area under the graph of <m:math xmlns:m=\"http://www.w3.org/1998/Math/MathML\"> <m:mi>A</m:mi> </m:math> A , in this contribution we show that the other famous concordance measure, Kendall’s <m:math xmlns:m=\"http://www.w3.org/1998/Math/MathML\"> <m:mi>τ</m:mi> </m:math> tau , allows for a simple geometric interpretation as well – it is inextricably linked to the surface area of <m:math xmlns:m=\"http://www.w3.org/1998/Math/MathML\"> <m:mi>A</m:mi> </m:math> A .","PeriodicalId":43690,"journal":{"name":"Dependence Modeling","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135604265","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
On copulas with a trapezoid support 关于具有梯形支撑的copula
IF 0.7
Dependence Modeling Pub Date : 2023-01-01 DOI: 10.1515/demo-2023-0101
P. Jaworski
{"title":"On copulas with a trapezoid support","authors":"P. Jaworski","doi":"10.1515/demo-2023-0101","DOIUrl":"https://doi.org/10.1515/demo-2023-0101","url":null,"abstract":"Abstract A family of bivariate copulas given by: for v + 2 u < 2 v+2ult 2 , C ( u , v ) = F ( 2 F − 1 ( v ∕ 2 ) + F − 1 ( u ) ) Cleft(u,v)=Fleft(2{F}^{-1}left(v/2)+{F}^{-1}left(u)) , where F F is a strictly increasing cumulative distribution function of a symmetric, continuous random variable, and for v + 2 u ≥ 2 v+2uge 2 , C ( u , v ) = u + v − 1 Cleft(u,v)=u+v-1 , is introduced. The basic properties and necessary conditions for absolute continuity of C C are discussed. Several examples are provided.","PeriodicalId":43690,"journal":{"name":"Dependence Modeling","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46671910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Mutual volatility transmission between assets and trading places 资产与交易场所之间的相互波动传导
Dependence Modeling Pub Date : 2023-01-01 DOI: 10.1515/demo-2022-0155
Andreas Masuhr, Mark Trede
{"title":"Mutual volatility transmission between assets and trading places","authors":"Andreas Masuhr, Mark Trede","doi":"10.1515/demo-2022-0155","DOIUrl":"https://doi.org/10.1515/demo-2022-0155","url":null,"abstract":"Abstract This article proposes a framework to model the mutual volatility transmission between multiple assets and multiple trading places in different time zones. The model is estimated using a dataset containing daily returns of three stock indices – the MSCI Japan, the EuroStoxx 50, and the S&amp;P 500 – each traded at three major trading places: the stock exchanges in Tokyo, London, and New York. Strong volatility transmission effects can be observed between New York and Tokyo, whereas current volatility in New York mostly depends on past volatility in New York. For the assets in consideration, spillovers are strong across trading zones, but weak across assets, suggesting a close connection between market places but only a loose volatility link between international stock indices. Volatility impulse response functions indicate a long-lasting and comparably large response of volatility in Tokyo, whereas they suggest a quicker volatility decay in London and New York.","PeriodicalId":43690,"journal":{"name":"Dependence Modeling","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135006813","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
An optimal transport-based characterization of convex order 基于输运的凸序最优表征
Dependence Modeling Pub Date : 2023-01-01 DOI: 10.1515/demo-2023-0102
Johannes Wiesel, Erica Zhang
{"title":"An optimal transport-based characterization of convex order","authors":"Johannes Wiesel, Erica Zhang","doi":"10.1515/demo-2023-0102","DOIUrl":"https://doi.org/10.1515/demo-2023-0102","url":null,"abstract":"Abstract For probability measures &lt;m:math xmlns:m=\"http://www.w3.org/1998/Math/MathML\"&gt; &lt;m:mi&gt;μ&lt;/m:mi&gt; &lt;m:mo&gt;,&lt;/m:mo&gt; &lt;m:mi&gt;ν&lt;/m:mi&gt; &lt;/m:math&gt; mu ,nu , and &lt;m:math xmlns:m=\"http://www.w3.org/1998/Math/MathML\"&gt; &lt;m:mi&gt;ρ&lt;/m:mi&gt; &lt;/m:math&gt; rho , define the cost functionals &lt;m:math xmlns:m=\"http://www.w3.org/1998/Math/MathML\" display=\"block\"&gt; &lt;m:mi&gt;C&lt;/m:mi&gt; &lt;m:mrow&gt; &lt;m:mo&gt;(&lt;/m:mo&gt; &lt;m:mrow&gt; &lt;m:mi&gt;μ&lt;/m:mi&gt; &lt;m:mo&gt;,&lt;/m:mo&gt; &lt;m:mi&gt;ρ&lt;/m:mi&gt; &lt;/m:mrow&gt; &lt;m:mo&gt;)&lt;/m:mo&gt; &lt;/m:mrow&gt; &lt;m:mo&gt;≔&lt;/m:mo&gt; &lt;m:munder&gt; &lt;m:mrow&gt; &lt;m:mi&gt;sup&lt;/m:mi&gt; &lt;/m:mrow&gt; &lt;m:mrow&gt; &lt;m:mi&gt;π&lt;/m:mi&gt; &lt;m:mo&gt;∈&lt;/m:mo&gt; &lt;m:mi mathvariant=\"normal\"&gt;Π&lt;/m:mi&gt; &lt;m:mrow&gt; &lt;m:mo&gt;(&lt;/m:mo&gt; &lt;m:mrow&gt; &lt;m:mi&gt;μ&lt;/m:mi&gt; &lt;m:mo&gt;,&lt;/m:mo&gt; &lt;m:mi&gt;ρ&lt;/m:mi&gt; &lt;/m:mrow&gt; &lt;m:mo&gt;)&lt;/m:mo&gt; &lt;/m:mrow&gt; &lt;/m:mrow&gt; &lt;/m:munder&gt; &lt;m:mo&gt;∫&lt;/m:mo&gt; &lt;m:mrow&gt; &lt;m:mo&gt;⟨&lt;/m:mo&gt; &lt;m:mrow&gt; &lt;m:mi&gt;x&lt;/m:mi&gt; &lt;m:mo&gt;,&lt;/m:mo&gt; &lt;m:mi&gt;y&lt;/m:mi&gt; &lt;/m:mrow&gt; &lt;m:mo&gt;⟩&lt;/m:mo&gt; &lt;/m:mrow&gt; &lt;m:mi&gt;π&lt;/m:mi&gt; &lt;m:mrow&gt; &lt;m:mo&gt;(&lt;/m:mo&gt; &lt;m:mrow&gt; &lt;m:mi mathvariant=\"normal\"&gt;d&lt;/m:mi&gt; &lt;m:mi&gt;x&lt;/m:mi&gt; &lt;m:mo&gt;,&lt;/m:mo&gt; &lt;m:mi mathvariant=\"normal\"&gt;d&lt;/m:mi&gt; &lt;m:mi&gt;y&lt;/m:mi&gt; &lt;/m:mrow&gt; &lt;m:mo&gt;)&lt;/m:mo&gt; &lt;/m:mrow&gt; &lt;m:mspace width=\"1.0em\" /&gt; &lt;m:mi mathvariant=\"normal\"&gt;and&lt;/m:mi&gt; &lt;m:mspace width=\"1em\" /&gt; &lt;m:mi&gt;C&lt;/m:mi&gt; &lt;m:mrow&gt; &lt;m:mo&gt;(&lt;/m:mo&gt; &lt;m:mrow&gt; &lt;m:mi&gt;ν&lt;/m:mi&gt; &lt;m:mo&gt;,&lt;/m:mo&gt; &lt;m:mi&gt;ρ&lt;/m:mi&gt; &lt;/m:mrow&gt; &lt;m:mo&gt;)&lt;/m:mo&gt; &lt;/m:mrow&gt; &lt;m:mo&gt;≔&lt;/m:mo&gt; &lt;m:munder&gt; &lt;m:mrow&gt; &lt;m:mi&gt;sup&lt;/m:mi&gt; &lt;/m:mrow&gt; &lt;m:mrow&gt; &lt;m:mi&gt;π&lt;/m:mi&gt; &lt;m:mo&gt;∈&lt;/m:mo&gt; &lt;m:mi mathvariant=\"normal\"&gt;Π&lt;/m:mi&gt; &lt;m:mrow&gt; &lt;m:mo&gt;(&lt;/m:mo&gt; &lt;m:mrow&gt; &lt;m:mi&gt;ν&lt;/m:mi&gt; &lt;m:mo&gt;,&lt;/m:mo&gt; &lt;m:mi&gt;ρ&lt;/m:mi&gt; &lt;/m:mrow&gt; &lt;m:mo&gt;)&lt;/m:mo&gt; &lt;/m:mrow&gt; &lt;/m:mrow&gt; &lt;/m:munder&gt; &lt;m:mo&gt;∫&lt;/m:mo&gt; &lt;m:mrow&gt; &lt;m:mo&gt;⟨&lt;/m:mo&gt; &lt;m:mrow&gt; &lt;m:mi&gt;x&lt;/m:mi&gt; &lt;m:mo&gt;,&lt;/m:mo&gt; &lt;m:mi&gt;y&lt;/m:mi&gt; &lt;/m:mrow&gt; &lt;m:mo&gt;⟩&lt;/m:mo&gt; &lt;/m:mrow&gt; &lt;m:mi&gt;π&lt;/m:mi&gt; &lt;m:mrow&gt; &lt;m:mo&gt;(&lt;/m:mo&gt; &lt;m:mrow&gt; &lt;m:mi mathvariant=\"normal\"&gt;d&lt;/m:mi&gt; &lt;m:mi&gt;x&lt;/m:mi&gt; &lt;m:mo&gt;,&lt;/m:mo&gt; &lt;m:mi mathvariant=\"normal\"&gt;d&lt;/m:mi&gt; &lt;m:mi&gt;y&lt;/m:mi&gt; &lt;/m:mrow&gt; &lt;m:mo&gt;)&lt;/m:mo&gt; &lt;/m:mrow&gt; &lt;m:mo&gt;,&lt;/m:mo&gt; &lt;/m:math&gt; Cleft(mu ,rho ):= mathop{sup }limits_{pi in Pi left(mu ,rho )}int langle x,yrangle pi left({rm{d}}x,{rm{d}}y)hspace{1.0em}{rm{and}}hspace{1em}Cleft(nu ,rho ):= mathop{sup }limits_{pi in Pi left(nu ,rho )}int langle x,yrangle pi left({rm{d}}x,{rm{d}}y), where &lt;m:math xmlns:m=\"http://www.w3.org/1998/Math/MathML\"&gt; &lt;m:mrow&gt; &lt;m:mo&gt;⟨&lt;/m:mo&gt; &lt;m:mrow&gt; &lt;m:mo&gt;⋅&lt;/m:mo&gt; &lt;m:mo&gt;,&lt;/m:mo&gt; &lt;m:mo&gt;⋅&lt;/m:mo&gt; &lt;/m:mrow&gt; &lt;m:mo&gt;⟩&lt;/m:mo&gt; &lt;/m:mrow&gt; &lt;/m:math&gt; langle cdot ,cdot rangle denotes the scalar product and &lt;m:math xmlns:m=\"http://www.w3.org/1998/Math/MathML\"&gt; &lt;m:mi mathvariant=\"normal\"&gt;Π&lt;/m:mi&gt; &lt;m:mrow&gt; &lt;m:mo&gt;(&lt;/m:mo&gt; &lt;m:mrow&gt; &lt;m:mo&gt;⋅&lt;/m:mo&gt; &lt;m:mo&gt;,&lt;/m:mo&gt; &lt;m:mo&gt;⋅&lt;/m:mo&gt; &lt;/m:mrow&gt; &lt;m:mo&gt;)&lt;/m:mo&gt; &lt;/m:mrow&gt; &lt;/m:math&gt; Pi left(cdot ,cdot ) is the set of couplings. We show that two probability measures &lt;m:math xmlns:m=\"http://www.w3.org/1998/Math/MathML\"&gt; &lt;m:mi&gt;μ&lt;/m:mi&gt; &lt;/m:math&gt; mu and &lt;m:math xmlns:m=\"http://www.w3.org/1998/Math/MathML\"&gt; &lt;m:mi&gt;ν&lt;/m:mi&gt; &lt;/m:math&gt; nu on &lt;m:math xmlns:m=\"http://www.w3.org/1998/Math/MathML\"&gt; &lt;m:msup&gt; &lt;m:mrow&gt; &lt;m:mi mathvariant=\"double-struck\"&gt;R&lt;/m:mi&gt; &lt;/m:mrow&gt; &lt;m:mr","PeriodicalId":43690,"journal":{"name":"Dependence Modeling","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135009168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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