Inference for Archimax copulas
نویسندگان
چکیده
منابع مشابه
Non-exchangeable random variables, Archimax copulas and their fitting to real data
In recent years copulas turned out to be a promising tool in multivariate modelling, mostly with applications in actuarial sciences and hydrology. In short, copula is a function which allows modelling dependence structure between stochastic variables. The main advantage is that the copula approach can split the problem of constructing multivariate probability distributions into a part containin...
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While there is substantial need for dependence models in higher dimensions, most existing models quickly become rather restrictive and barely balance parsimony and flexibility. Hierarchical constructions may improve on that by grouping variables in different levels. In this paper, the new class of hierarchical Kendall copulas is proposed and discussed. Hierarchical Kendall copulas are built up ...
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Statistical inference for copulas has been addressed in various research papers. Due to the complicated theoretical results, studies have been carried out mainly in the bivariate case, be it properties of estimators or goodness-of-fit tests. However, from a practical point of view, higher dimensions are of interest. This work presents the results of large-scale simulation studies with particula...
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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, several consistent estimators of A are available. Most of them are variants of the estimators due to Pickands [Bull. In this paper, rank-based versions of these esti-mators are proposed for the more commo...
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ژورنال
عنوان ژورنال: The Annals of Statistics
سال: 2020
ISSN: 0090-5364
DOI: 10.1214/19-aos1836