A Variational Approach for Modeling High-dimensional Spatial Generalized
Linear Mixed Models
A Variational Approach for Modeling High-dimensional Spatial Generalized
Linear Mixed Models
Gaussian and discrete non-Gaussian spatial datasets are prevalent across many fields such as public health, ecology, geosciences, and social sciences. Bayesian spatial generalized linear mixed models (SGLMMs) are a flexible class of models designed for these data, but SGLMMs do not scale well, even to moderately large datasets. State-of-the-art scalable …