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Bayesian Modular Inference for Copula Models with Potentially Misspecified Marginals
Copula models of multivariate data are popular because they allow separate specification of marginal distributions and the copula function. These components can be treated as inter-related modules in a modified Bayesian inference approach called ''cutting feedback'' that is robust to their misspecif
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