Conditions for the asymptotic semiparametric efficiency of an omnibus estimator of dependence parameters in copula model
This thesis describes the properties of a moment-based technique for estimating the dependence param...
summary:In the paper we investigate properties of maximum pseudo-likelihood estimators for the copul...
summary:We introduce new estimates and tests of independence in copula models with unknown margins u...
Recent literature on semiparametric copula models focused on the situation when the marginals are sp...
The authors define a new semiparametric Archimedean copula family which has a flexible dependence st...
Recently a new way of modeling dependence has been introduced considering a sequence of parametric c...
The authors define a new semiparametric Archimedean copula family which has a flexible dependence st...
A new way of choosing a suitable copula to model dependence is introduced. Instead of relying on a g...
A new way of choosing a suitable copula to model dependence is introduced. Instead of relying on a g...
Copulas are used to specify dependence between two or more random variables. The last few years have...
Recent literature on semiparametric copula models focused on the situation when the marginals are sp...
As Prof. Mikosch correctly points out, there exists very little sound statistical theory on modellin...
This paper studies the estimation of copula-based semi parametric stationary Markov models. Describe...
AbstractFor the study of dynamic dependence structures, the authors introduce the concept of a pseud...
AbstractThe manner in which two random variables influence one another often depends on covariates. ...
This thesis describes the properties of a moment-based technique for estimating the dependence param...
summary:In the paper we investigate properties of maximum pseudo-likelihood estimators for the copul...
summary:We introduce new estimates and tests of independence in copula models with unknown margins u...
Recent literature on semiparametric copula models focused on the situation when the marginals are sp...
The authors define a new semiparametric Archimedean copula family which has a flexible dependence st...
Recently a new way of modeling dependence has been introduced considering a sequence of parametric c...
The authors define a new semiparametric Archimedean copula family which has a flexible dependence st...
A new way of choosing a suitable copula to model dependence is introduced. Instead of relying on a g...
A new way of choosing a suitable copula to model dependence is introduced. Instead of relying on a g...
Copulas are used to specify dependence between two or more random variables. The last few years have...
Recent literature on semiparametric copula models focused on the situation when the marginals are sp...
As Prof. Mikosch correctly points out, there exists very little sound statistical theory on modellin...
This paper studies the estimation of copula-based semi parametric stationary Markov models. Describe...
AbstractFor the study of dynamic dependence structures, the authors introduce the concept of a pseud...
AbstractThe manner in which two random variables influence one another often depends on covariates. ...
This thesis describes the properties of a moment-based technique for estimating the dependence param...
summary:In the paper we investigate properties of maximum pseudo-likelihood estimators for the copul...
summary:We introduce new estimates and tests of independence in copula models with unknown margins u...