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Vine Copulas as Differentiable Computational Graphs

open access: yes
Vine copulas are sophisticated models for multivariate distributions and are increasingly used in machine learning. To facilitate their integration into modern ML pipelines, we introduce the vine computational graph, a DAG that abstracts the multilevel vine structure and associated computations.
Cheng, Tuoyuan   +3 more
openaire   +2 more sources

Bi-factor and Second-Order Copula Models for Item Response Data. [PDF]

open access: yesPsychometrika, 2023
Kadhem SH, Nikoloulopoulos AK.
europepmc   +1 more source

Value-at-Risk with Vine Copulas

open access: yes, 2023
Especially when considering a portfolio with multiple assets the dependence structure in-between them is crucial regarding the grade of diversification and risk assessment. Models which consist of the multivariate normal distribution are popular because of their simplicity and fast calculation time.
openaire   +1 more source

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