1 citations · 1 across the 4 of their papers we have counts for
4 papers
Bayesian Modular Inference for Copula Models with Potentially Misspecified Marginals
Lucas Kock, David T. Frazier, Michael Stanley Smith +1
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…
Conjugating Variational Inference for Large Mixed Multinomial Logit Models and Consumer Choice
Weiben Zhang, Ruben Loaiza-Maya, Michael Stanley Smith +1
Heterogeneity in multinomial choice data is often accounted for using logit models with random coefficients. Such models are called "mixed", but they can be difficult to estimate f…
A Tractable Unified Skew-t Distribution and Its Copula for Heterogeneous Asymmetries
Lin Deng, Michael Stanley Smith, Worapree Maneesoonthorn
Multivariate distributions that allow for asymmetry and heavy tails are important building blocks in many econometric and statistical models. The Unified Skew-t (UST) is a promisin…
Large Skew-t Copula Models and Asymmetric Dependence in Intraday Equity Returns
Lin Deng, Michael Stanley Smith, Worapree Maneesoonthorn
Skew-t copula models are attractive for the modeling of financial data because they allow for asymmetric and extreme tail dependence. We show that the copula implicit in the skew-t…