A pair-copula construction is a decomposition of a multivariate copula into a structured system, called regular vine, of bivariate copulae or pair-copulae. The standard practice is to model these pair-copulae parametrically, inducing a model risk, with errors potentially propagating throughout the vine structure. The empirical pair-copula provides a nonparametric alternative, which is conjectured to still achieve the parametric convergence rate. Its main advantage for the user is that it does not require the choice of parametric models for each of the pair-copulae constituting the construction. It can be used as a basis for inference on dependence measures, for selecting an appropriate vine structure, and for testing for conditional indepen...
A common assumption in pair-copula constructions is that the copula of the conditional distribution ...
<p>Pair-copula constructions are flexible dependence models that use bivariate copulas as building b...
In recent years, conditional copulas, that allow dependence between variables to vary according to t...
A pair-copula construction is a decomposition of a multivariate copula into a structured system, cal...
AbstractDue to their high flexibility, yet simple structure, pair-copula constructions (PCCs) are be...
This thesis contributes to research in multivariate statistics by developing regular vine copula-bas...
Nagler T, Schellhase C, Czado C. Nonparametric estimation of simplified vine copula models: comparis...
Copulas are important models that allow to capture the dependence among variables. There are many ty...
Pair-copula constructions (or vine copulas) are structured, in the layout of vines, with bivariate c...
While there is a multitude of bivariate copula, the class of multivariate copulae is still quite res...
Pair-copula constructions (or vine copulas) are structured, in the layout of vines, with bivariate c...
So called pair copula constructions (PCCs), specifying multivariate distributions only in terms of b...
This textbook provides a step-by-step introduction to the class of vine copulas, their statistical i...
AbstractPair-copula constructions (PCCs) offer great flexibility in modeling multivariate dependence...
Dependence Modeling with Copulas covers the substantial advances that have taken place in the field ...
A common assumption in pair-copula constructions is that the copula of the conditional distribution ...
<p>Pair-copula constructions are flexible dependence models that use bivariate copulas as building b...
In recent years, conditional copulas, that allow dependence between variables to vary according to t...
A pair-copula construction is a decomposition of a multivariate copula into a structured system, cal...
AbstractDue to their high flexibility, yet simple structure, pair-copula constructions (PCCs) are be...
This thesis contributes to research in multivariate statistics by developing regular vine copula-bas...
Nagler T, Schellhase C, Czado C. Nonparametric estimation of simplified vine copula models: comparis...
Copulas are important models that allow to capture the dependence among variables. There are many ty...
Pair-copula constructions (or vine copulas) are structured, in the layout of vines, with bivariate c...
While there is a multitude of bivariate copula, the class of multivariate copulae is still quite res...
Pair-copula constructions (or vine copulas) are structured, in the layout of vines, with bivariate c...
So called pair copula constructions (PCCs), specifying multivariate distributions only in terms of b...
This textbook provides a step-by-step introduction to the class of vine copulas, their statistical i...
AbstractPair-copula constructions (PCCs) offer great flexibility in modeling multivariate dependence...
Dependence Modeling with Copulas covers the substantial advances that have taken place in the field ...
A common assumption in pair-copula constructions is that the copula of the conditional distribution ...
<p>Pair-copula constructions are flexible dependence models that use bivariate copulas as building b...
In recent years, conditional copulas, that allow dependence between variables to vary according to t...