Bayesian Modular Inference for Copula Models with Potentially Misspecified Marginals
边际可能误设的 Copula 模型的贝叶斯模块化推断
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 misspecification. Recent work uses a two module approach, where all $d$ marginals form a single module, to robustify inference for the marginals against copula function misspecification,…