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Asymptotic properties of the Bernstein density copula for dependent data [PDF]
Copulas are extensively used for dependence modeling. In many cases the data does not reveal how the dependence can be modeled using a particular parametric copula. Nonparametric copulas do not share this problem since they are entirely data based.
ROMBOUTS, Jeroen V.K. +2 more
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Nonparametric estimation of pair-copula constructions with the empirical pair-copula
, 2012 A pair-copula construction is a decomposition of a multivariate copula into a structured system, called regular vine, of bivariate copulae or paircopulae.
Segers, Johan, Hoebak Haff, Ingrid
core
, 2019 Preterm births represent a serious medical issue since they can affect the health of the mother and the fetus. Our idea is to study the dependence between preterm births in repeated pregnancies using a vine copula approach.
Luciana Dalla Valle, Rosario Barone
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Tail dependence functions and vine copulas
Tail dependence and conditional tail dependence functions describe, respectively, the tail probabilities and conditional tail probabilities of a copula at various relative scales.
Joe, Harry +2 more
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Vine copula based structural equation models
Computational Statistics & Data Analysisopenaire +3 more sources
D-Vine Copula Based Quantile Regression [PDF]
Computational Statistics and Data Analysis, 2017 Quantile regression, that is the prediction of conditional quantiles, has steadily gained importance in statistical modeling and financial applications. The authors introduce a new semiparametric quantile regression method based on sequentially fitting a likelihood optimal D-vine copula to given data resulting in highly flexible models with easily ...
Claudia Czado, Daniel Kraus
exaly +6 more sources
Modelling Mortality Dependence: An Application of Dynamic Vine Copula
Insurance: Mathematics and Economics, 2021 Vine copula, constructed from bivariate copulas, provides great exibility in modelling complex high-dimensional dependence. When applied to multi- population mortality modelling, vine copula yields signi_cant improvement over traditional multivariate ...
Rui Zhou
exaly +2 more sources
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Vine Copula Models with GLM and Sparsity
Communications in Statistics - Theory and Methods, 2016Vine copula provides a flexible tool to capture asymmetry in modelling multivariate distributions. Nevertheless, its flexibility is achieved at the expense of exponentially increasing complexity of the model. To alleviate this issue, the simplifying assumption (SA) is commonly adapted in specific applications of vine copula models.
Dezhao Han, Ken Seng Tan, Chengguo Weng
openaire +1 more source
2013
Vine copula models have proven themselves as a very flexible class of multivariate copula models with regard to symmetry and tail dependence for pairs of variables. The full specification of a vine model requires the choice of a vine tree structure, the copula families for each pair copula term and their corresponding parameters.
Claudia Czado +2 more
openaire +1 more source
Vine copula models have proven themselves as a very flexible class of multivariate copula models with regard to symmetry and tail dependence for pairs of variables. The full specification of a vine model requires the choice of a vine tree structure, the copula families for each pair copula term and their corresponding parameters.
Claudia Czado +2 more
openaire +1 more source