AbstractConditions are given under which the empirical copula process associated with a random sample from a bivariate continuous distribution has a smaller asymptotic covariance function than the standard empirical process based on observations from the copula. Illustrations are provided and consequences for inference are outlined
The modelling of dependence relations between random variables is one of the most widely studied sub...
The empirical beta copula is a simple but effective smoother of the empirical copula. Because it is ...
The empirical copula has proved to be useful in the construction and understanding of many statistic...
Conditions are given under which the empirical copula process associated with a random sample from a...
Genest and Segers (2010) gave conditions under which the empirical copula process associated with a ...
AbstractConditions are given under which the empirical copula process associated with a random sampl...
When the copula of the conditional distribution of two random variables given a covariate does not d...
The empirical copula process plays a central role for statistical inference on copulas. The main pur...
At the heart of the copula methodology in statistics is the idea of separating marginal distribution...
Given a sample from a continuous multivariate distribution FF, the uniform random variates generated...
At the heart of the copula methodology in statistics is the idea of separating marginal distribution...
Weak convergence of the empirical copula process is shown to hold under the assumption that the firs...
Given a sample from a multivariate distribution F, the uniform random variates generated independent...
In this thesis, we are concerned with strong approximations of the empirical copula process, possibl...
The asymptotic behavior of the empirical copula constructed from residuals of stochastic volatility ...
The modelling of dependence relations between random variables is one of the most widely studied sub...
The empirical beta copula is a simple but effective smoother of the empirical copula. Because it is ...
The empirical copula has proved to be useful in the construction and understanding of many statistic...
Conditions are given under which the empirical copula process associated with a random sample from a...
Genest and Segers (2010) gave conditions under which the empirical copula process associated with a ...
AbstractConditions are given under which the empirical copula process associated with a random sampl...
When the copula of the conditional distribution of two random variables given a covariate does not d...
The empirical copula process plays a central role for statistical inference on copulas. The main pur...
At the heart of the copula methodology in statistics is the idea of separating marginal distribution...
Given a sample from a continuous multivariate distribution FF, the uniform random variates generated...
At the heart of the copula methodology in statistics is the idea of separating marginal distribution...
Weak convergence of the empirical copula process is shown to hold under the assumption that the firs...
Given a sample from a multivariate distribution F, the uniform random variates generated independent...
In this thesis, we are concerned with strong approximations of the empirical copula process, possibl...
The asymptotic behavior of the empirical copula constructed from residuals of stochastic volatility ...
The modelling of dependence relations between random variables is one of the most widely studied sub...
The empirical beta copula is a simple but effective smoother of the empirical copula. Because it is ...
The empirical copula has proved to be useful in the construction and understanding of many statistic...
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