Variational Approximations for Generalized Linear Latent Variable Models
Generalized linear latent variable models (GLLVMs) are a powerful class of models for understanding the relationships among multiple, correlated responses. Estimation, however, presents a major challenge, as the marginal likelihood does not possess a closed form for nonnormal responses. We propose a variational approximation (VA) method for estimating GLLVMs. For the common cases of binary, ordinal, and overdispersed count data, we derive fully closed-form approximations to the marginal...[Show more]
|Collections||ANU Research Publications|
|Source:||Journal of Computational and Graphical Statistics|
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