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Jackknife Empirical Likelihood for Parametric Copulas
Copulas Empirical likelihood Interval estimation Jackknife
2016/1/19
For fitting a parametric copula to multivariate data, a popular way is to employ the so-called pseudo maximum likelihood estimation proposed by Genest, Ghoudi and Rivest (1995). Although interval esti...
Nonparametric estimation of multivariate extreme-value copulas
empirical copula extreme-value copula Pickands dependence function
2011/7/19
Extreme-value copulas arise in the asymptotic theory for componentwise maxima of independent random samples. An extreme-value copula is determined by its Pickands dependence function, which is a funct...
Large-sample tests of extreme-value dependence for multivariate copulas
max-stability multiplier central limit theorem pseudo-observations ranks
2011/6/17
Starting from the characterization of extreme-value copulas based on maxstability,
large-sample tests of extreme-value dependence for multivariate copulas
are studied. The two key ingredients of the...
Vine copulas as a mean for the construction of high dimensional probability distribution associated to a Markov Network
Copula decomposition t-cherry junction tree Markov network Cherry-wine probability distribution Graphical models
2011/6/17
Building higher-dimensional copulas is generally recognized as a difficult
problem. Regular-vines using bivariate copulas provide a flexible class of high-dimensional
dependency models. In large dim...
Some Properties of Schur-Constant Survival Models and their Copulas
Properties Schur-Constant Survival Models Copulas
2009/9/17
Some Properties of Schur-Constant Survival Models and their Copulas。
On Grade Transformation and its Implications for Copulas
Grade Transformation Implications Copulas
2009/9/17
On Grade Transformation and its Implications for Copulas。
Rank-based inference for bivariate extreme-value copulas
Asymptotic theory copula extreme-value distribution non-parametric estimation Pickands dependence function rank-based inference
2010/4/30
Consider a continuous random pair (X,Y ) whose dependence is
characterized by an extreme-value copula with Pickands dependence
function A. When the marginal distributions of X and Y are known,
seve...