Statistical Dependence Modeling

Edited by Thomas Nagler (), Dorota Kurowicka (), Roger Cooke () and Harry Joe ()

in Springer Books from Springer

Date: 2026
ISBN: 978-3-032-14252-8
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Chapters in this book:

Growth Cycle of Vine Copulas

Kjersti Aas, Roger Cooke, Harry Joe, Dorota Kurowicka and Thomas Nagler

A Decade of Elevating (with) Vine Copulas

Nicole Barthel, Eike Brechmann and Dominik Müller

Stochastic Simulation Inference Algorithm in Restricted Pair Copula Bayesian Network with Single Root Node

Panagiotis Basiouras Serrano and Dorota Kurowicka

Gibbs Copulas

Manfred Denker and Aleksey Min

Diagnostics for the Validity of the Simplifying Assumption for Vine Copulas

Harry Joe

Identifiability and the Simplifying Assumption

Roger Cooke and Tim Bedford

Measures of Non-simplifyingness for Conditional Copulas and Vines

Alexis Derumigny

On Dimension Reduction in Conditional Dependence Models

Thomas Nagler, Gerda Claeskens and Irène Gijbels

Copula Structural Equation Models for Mediation Pathway Analysis

Canyi Chen, Ritoban Kundu, Wei Hao and Peter X. K. Song

Cluster-Specific Ranking and Variable Importance for Scottish Regional Deprivation via Vine Mixtures

Özge Şahin, Ozan Evkaya and Ariane Hanebeck

A Flexible Control Function Approach for Survival Data Subject to Different Types of Censoring

Ilias Willems, Sara Rutten, Gilles Crommen and Ingrid Van Keilegom

Vine Copula-Based Probabilistic Weather Forecasting: Review, Challenges, and Future Work

Annette Möller, David Jobst and Ferdinand Buchner

Generalized Precision Matrices for Non-gaussian Distributions: Theory and Portfolio Applications

Karoline Bax, Alessandro Fulci, Sandra Paterlini and Emanuele Taufer

LogTukey-Type Distributions as Models for Operational Losses

Matthias Fischer

Marginal Data Augmentation for Efficient Bayesian Modeling of Counts and Rates with a Demographic Application

Gregor Zens and Sylvia Frühwirth-Schnatter

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DOI: 10.1007/978-3-032-14252-8

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