In mixed company: Bayesian inference for bivariate conditional copula models with discrete and continuous outcomes

DOI10.1016/j.jmva.2012.03.010zbMath1244.62031OpenAlexW1966510834MaRDI QIDQ443781

Avideh Sabeti, V. Radu Craiu

Publication date: 13 August 2012

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jmva.2012.03.010

zbMATH Keywords

cubic splinesadaptive Markov chain Monte Carlodeviance information criterionmixed outcomes

Mathematics Subject Classification ID

Related Items (15)

Approximate Bayesian Computation for Copula Estimation ⋮ Simultaneous inference in structured additive conditional copula regression models: a unifying Bayesian approach ⋮ A generative approach to modeling data with quantitative and qualitative responses ⋮ Bayesian inference for conditional copulas using Gaussian process single index models ⋮ Fully and empirical Bayes approaches to estimating copula-based models for bivariate mixed outcomes using Hamiltonian Monte Carlo ⋮ Statistical testing of covariate effects in conditional copula models ⋮ Boosting Distributional Copula Regression ⋮ Marginally calibrated response distributions for end-to-end learning in autonomous driving ⋮ About tests of the ``simplifying assumption for conditional copulas ⋮ Bayesian Nonparametric Modeling of Conditional Multidimensional Dependence Structures ⋮ Single-index copulas ⋮ Implicit copulas from Bayesian regularized regression smoothers ⋮ Generalized additive models for conditional dependence structures ⋮ Generalized Additive Models for Pair-Copula Constructions ⋮ Approximate Bayesian conditional copulas

Uses Software

• BayesDA

Cites Work

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