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Posterior Simulation in the Generalized Linear Mixed Model With Semiparametric Random Effects
Journal of Computational And Graphical Statistics
Generalized linear mixed models with semiparametric random effects are useful in a wide variety of Bayesian applications. When the random effects arise from a mixture of Dirichlet process (MDP) model with normal base measure, Gibbs sampling algorithms based on the Pólya urn scheme are often used to simulate posterior draws in conjugate models (essentially, linear regression models and models for binary outcomes). In the non-conjugate case, the algorithms proposed by MacEachern and Müller (1998)doi:10.1198/106186008x319854 fatcat:vzm44sw7bngjxovukb3ea74l3y