zinbcdpmm: Bayesian ZINB-Ordinal Joint Model with CDPMM Random Effects
Fits a Bayesian joint model for longitudinal zero-inflated
negative binomial (ZINB) and ordinal outcomes with shared random effects
under a centered Dirichlet process mixture model (CDPMM) prior. Provides
a blocked Gibbs sampler with Polya-Gamma (PG) and Chinese restaurant table
data augmentation, plus helpers for simulation and posterior summaries
based on the deviance information criterion (DIC), the widely applicable
information criterion (WAIC) and the leave-one-out information criterion
(LOOIC). The PG augmentation follows Polson, Scott and Windle (2013)
<doi:10.1080/01621459.2013.829001>, the zero-inflated negative binomial
construction follows Neelon (2019) <doi:10.1214/18-BA1132>, and the
centered Dirichlet process mixture prior follows Tang, Tang and Pan (2014)
<doi:10.1016/j.csda.2014.02.015>.
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