Bayesian spatiotemporal modeling using hierarchical spatial priors, with applications to functional magnetic resonance imaging (with discussion)

Keyphrases

• Functional Magnetic Resonance Imaging 100%
• Spatial Prior 100%
• Bayesian Spatial Analysis 100%
• Spatiotemporal 33%
• Spatial Dependence 33%
• Markov Chain Monte Carlo Algorithm 33%
• Posterior Distribution 33%
• Parcellation 33%
• Indicator Variables 33%
• Areal Models 33%
• Bayesian Variable Selection 33%
• Hierarchical Prior 33%
• Ising Prior 33%
• Popular 33%
• Binary Indicators 33%
• Variable Selection Model 33%

Mathematics

• Bayesian 100%
• Magnetic Resonance Imaging 100%
• Voxel 66%
• Markov Chain Monte Carlo 33%
• Posterior Distribution 33%
• Indicator Variable 33%
• Bayesian Variable Selection 33%
• Monte Carlo Algorithm 33%
• Simulated Data 33%

Earth and Planetary Sciences

• Spatial Dependence 100%
• Markov Chain Monte Carlo 100%