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Efficiently sampling nested Archimedean copulas
Computational Statistics and Data Analysis, 2011zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Marius Höfert
exaly +2 more sources
Estimating Archimedean Copulas in High Dimensions
Scandinavian Journal of Statistics, 2012Abstract. This article presents a novel estimation procedure for high‐dimensional Archimedean copulas. In contrast to maximum likelihood estimation, the method presented here does not require derivatives of the Archimedean generator. This is computationally advantageous for high‐dimensional Archimedean copulas in which higher‐order derivatives are ...
Ulrich Stadtmüller
exaly +3 more sources
Geostatistical prediction through convex combination of Archimedean copulas
, 2021A common problem in geostatistics is to interpolate a variable at unsampled locations using available data. Kriging has been the conventional method of solving this problem by providing the weighted average of samples, which is determined by minimizing ...
B. Sohrabian
semanticscholar +1 more source
Portfolio credit risk with Archimedean copulas: asymptotic analysis and efficient simulation
Annals of Operations Research, 2022In this paper, we study large losses arising from defaults of a credit portfolio. We assume that the portfolio dependence structure is modelled by the Archimedean copula family as opposed to the widely used Gaussian copula.
Hengxin Cui, K. S. Tan, Fan Yang
semanticscholar +1 more source
On a Family of Log-Gamma-Generated Archimedean Copulas
North American Actuarial Journal, 2021Modeling dependence structure among various risks, especially the measure of tail dependence and the aggregation of risks, is crucial for risk management.
Yaming Yang, Shuanming Li
semanticscholar +1 more source
Hierarchical Archimedean copulas through multivariate compound distributions
Insurance: Mathematics and Economics, 2017Hélène Cossette +2 more
exaly +2 more sources
On the use of Archimedean copulas for insurance modelling
Annals of Actuarial Science, 2020In this paper, we explore the use of an extensive list of Archimedean copulas in general and life insurance modelling. We consider not only the usual choices like the Clayton, Gumbel–Hougaard, and Frank copulas but also several others which have not ...
Dulanjali Kularatne +2 more
semanticscholar +1 more source
IGNIS: a robust neural network framework for constrained parameter estimation in Archimedean copulas
Communications in Statistics - Simulation and ComputationClassical estimators, the cornerstones of statistical inference, face insurmountable challenges when applied to important emerging classes of Archimedean copulas.
Agnideep Aich
semanticscholar +1 more source