COPAR -- multivariate time series modeling using the copula autoregressive model

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Cites Work

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Pair-copula constructions of multiple dependence
Selecting and estimating regular vine copulae and application to financial returns
Likelihood Ratio Tests for Model Selection and Non-Nested Hypotheses
Estimation of copula-based semiparametric time series models
Simplified pair copula constructions -- limitations and extensions
A review of copula models for economic time series
Copula-based semiparametric models for multivariate time series
Beyond simplified pair-copula constructions
An introduction to copulas.
On the simplified pair-copula construction -- simply useful or too simplistic?
Copulas and Markov processes
A parameterization of positive definite matrices in terms of partial correlation vines
Vines -- a new graphical model for dependent random variables.
Statistical properties of parametric estimators for Markov chain vectors based on copula models
Probability density decomposition for conditionally dependent random variables modeled by vines
Modeling statistical dependence of Markov chains via copula models
Selection of Vine Copulas
On Kendall's Autocorrelations
COPULA-BASED CHARACTERIZATIONS FOR HIGHER ORDER MARKOV PROCESSES
Truncated regular vines in high dimensions with application to financial data
Modeling Financial Time Series with S-PLUS®
Uncertainty Analysis with High Dimensional Dependence Modelling
Kendall's tau for serial dependence
Distributions Generated by Perturbation of Symmetry with Emphasis on a Multivariate Skewt-Distribution
Modeling Longitudinal Data Using a Pair-Copula Decomposition of Serial Dependence
Strictly Proper Scoring Rules, Prediction, and Estimation