Overview
Brian Neelon is a biostatistician (Medical University of South Carolina; previously Duke University), working on Bayesian hierarchical models for health and spatial data — mixtures, zero-inflated and count models, and areal spatial analysis.
Key Contributions / Features
- Multivariate spatial mixture model for areal data (Neelon-Gelfand 2014): with Gelfand and Miranda, CAR-smoothed finite-mixture modelling of correlated continuous outcomes.
- Work on Bayesian zero-inflated/hurdle models, spatial and spatio-temporal health-services models, and latent-class methods.
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