DOI10.1016/j.csda.2012.08.010zbMath1400.62114arXiv1202.2002OpenAlexW2030338847MaRDI QIDQ80568
J. Dißmann, Dorota Kurowicka, C. Czado, E.C. Brechmann, Claudia Czado, J. Dißmann, Eike Christian Brechmann, Dorota Kurowicka
Publication date: March 2013
Published in: Computational Statistics & Data Analysis, Computational Statistics and Data Analysis (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1202.2002
Beyond Linear Dynamic Functional Connectivity: A Vine Copula Change Point Model,
Copula-based link functions in binary regression models,
Bi-factor and second-order copula models for item response data,
Modelling credit card exposure at default using vine copula quantile regression,
Dependence Model Assessment and Selection with DecoupleNets,
A semiparametric copula method for Cox models with covariate measurement error,
A multivariate volatility vine copula model,
Estimation of high-order moment-independent importance measures for Shapley value analysis,
Nonparametric estimation of simplified vine copula models: comparison of methods,
Modeling multivariate cybersecurity risks,
Copula diagnostics for asymmetries and conditional dependence,
Optimizing effective numbers of tests by vine copula modeling,
Detecting and modeling critical dependence structures between random inputs of computer models,
Regime switches in the dependence structure of multidimensional financial data,
Parsimonious parameterization of correlation matrices using truncated vines and factor analysis,
Simplified R-vine based forward regression,
Nonparametric estimation of pair-copula constructions with the empirical pair-copula,
Dissimilarity functions for rank-invariant hierarchical clustering of continuous variables,
Robust dependence modeling for high-dimensional covariance matrices with financial applications,
Robust optimization of mixed CVaR STARR ratio using copulas,
Specification of informative prior distributions for multinomial models using vine copulas,
Bayesian model selection of regular vine copulas,
Regular vines with strongly chordal pattern of (conditional) independence,
Default probability estimation via pair copula constructions,
R‐vine models for spatial time series with an application to daily mean temperature,
Smooth nonparametric Bernstein vine copulas,
Model selection for discrete regular vine copulas,
Modeling vine-production function: an approach based on vine copula,
Structure learning in Bayesian networks using regular vines,
Vine copula based likelihood estimation of dependence patterns in multivariate event time data,
Comorbidity of chronic diseases in the elderly: patterns identified by a copula design for mixed responses,
Copula-Based Regression Estimation and Inference,
Simplified pair copula constructions -- limitations and extensions,
Factor copula models for multivariate data,
Dependence modelling in ultra high dimensions with vine copulas and the graphical Lasso,
Vine copula statistical disclosure control for mixed-type data,
Dynamic D-vine copula model with applications to Value-at-Risk (VaR),
Robust DC optimal power flow with modeling of solar power supply uncertainty via R-vine copulas,
Truncated regular vines in high dimensions with application to financial data,
A Time-Heterogeneous D-Vine Copula Model for Unbalanced and Unequally Spaced Longitudinal Data,
On the quantification and efficient propagation of imprecise probabilities with copula dependence,
Deviation measure in second‐order stochastic dominance with an application to enhanced indexing,
Covariance model simulation using regular vines,
Intermuscular coupling network analysis of upper limbs based on R-vine copula transfer entropy,
Model distances for vine copulas in high dimensions,
Estimating non-simplified vine copulas using penalized splines,
Vine copula approximation: a generic method for coping with conditional dependence,
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Parameter estimation for pair-copula constructions,
Construction of leading economic index for recession prediction using vine copulas,
Risk aggregation in non-life insurance: standard models vs. internal models,
MODELLING MORTALITY DEPENDENCE WITH REGIME-SWITCHING COPULAS,
Statistical arbitrage with vine copulas,
Vine copula regression for observational studies,
A Bayesian hierarchical copula model,
Data-driven polynomial chaos expansion for machine learning regression,
Pair-copula models for analyzing family data,
DYNAMIC ASSET CORRELATIONS BASED ON VINES,
Analysis of long-term natural gas contracts with vine copulas in optimization portfolio problems,
Sequential truncation of \(R\)-vine copula mixture model for high-dimensional datasets,
Copula directed acyclic graphs,
Hierarchical Kendall copulas: Properties and inference,
Model selection of copulas: AIC versus a cross validation copula information criterion,
On the structure and estimation of hierarchical Archimedean copulas,
Model selection in sparse high-dimensional vine copula models with an application to portfolio risk,
Prediction based on conditional distributions of vine copulas,
Estimating standard errors in regular vine copula models,
Common sampling orders of regular vines with application to model selection,
Vine Copula Specifications for Stationary Multivariate Markov Chains,
Conditional copula simulation for systemic risk stress testing,
Testing the simplifying assumption in high-dimensional vine copulas,
Evading the curse of dimensionality in nonparametric density estimation with simplified vine copulas,
A copula-based GLMM model for multivariate longitudinal data with mixed-types of responses,
pyvine: the Python package for regular vine copula modeling, sampling and testing,
Forecasting VaR and ES of stock index portfolio: a vine copula method,
Stationary vine copula models for multivariate time series,
Pair Copula Constructions for Insurance Experience Rating,
A geometric investigation into the tail dependence of vine copulas,
Modelling mortality dependence: an application of dynamic vine copula,
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A mixture of regular vines for multiple dependencies,
Copula approaches for modeling cross-sectional dependence of data breach losses,
Market risk forecasting for high dimensional portfolios via factor copulas with GAS dynamics,
Robust omega ratio optimization using regular vines,
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VineCopula,
The bivariate K-finite normal mixture ‘blanket’ copula,
Representing Sparse Gaussian DAGs as Sparse R-Vines Allowing for Non-Gaussian Dependence,
Informative goodness-of-fit for multivariate distributions,
Extreme dependence in investor attention and stock returns – consequences for forecasting stock returns and measuring systemic risk,
Simulation methods for robust risk assessment and the distorted mix approach,
Worst-Case Expected Shortfall with Univariate and Bivariate Marginals,
Selection of sparse vine copulas in high dimensions with the Lasso,
A copula‐based risk aggregation model,
Selection of Vine Copulas,
Vine copula graphical models in the construction of biological networks,
A goodness-of-fit test for regular vine copula models,
CD-vine model for capturing complex dependence,
Preface to special issue on high-dimensional dependence and copulas,
Truncation of vine copulas using fit indices,
Efficient information based goodness-of-fit tests for vine copula models with fixed margins: a comprehensive review,
Structured factor copula models: theory, inference and computation,
Variational inference with vine copulas: an efficient approach for Bayesian computer model calibration