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Variational Approximations for Generalized Linear Latent Variable Models

Hui, Francis; Warton, David I.; Ormerod, John T.; Haapaniemi, Viivi; Taskinen, Sara


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]

CollectionsANU Research Publications
Date published: 2017
Type: Journal article
Source: Journal of Computational and Graphical Statistics
DOI: 10.1080/10618600.2016.1164708


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