Applying an Intrinsic Conditional Autoregressive Reference Prior for Areal Data
Bayesian hierarchical models are useful for modeling spatial data because they have flexibility to accommodate complicated dependencies that are common to spatial data. In particular, intrinsic conditional autoregressive (ICAR) models are commonly assigned as priors for spatial random effects in hie...
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Virginia Tech
2019
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| Online Access: | http://hdl.handle.net/10919/91385 |