Regular Vine Copulas with the simplifying assumption, time-variation, and mixed discrete and continuous margins

This thesis extends the theory of pair-copula constructions (PCCs) based on regular vines (R-vines) in several aspects. We develop PCCs for models with both discrete and continuous one dimensional marginal distributions and present algorithms for an implementation in statistical software. Also, we identify models for which the simplifying assumption that copulas corresponding to conditional distributions are constant holds. A model with Markov-Switching R-vine copulas is developed, and we consider applications to exchange rate data and data from the Second Longitudinal Study of Aging.

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