Objective Bayesian analysis for Gaussian hierarchical models with intrinsic conditional autoregressive priors

DOI10.1214/18-BA1107zbMath1409.62187MaRDI QIDQ1757670

Marco A. R. Ferreira, Matthew J. Keefe, Christopher T. Franck

Publication date: 15 January 2019

Published in: Bayesian Analysis (Search for Journal in Brave)

Full work available at URL: https://projecteuclid.org/euclid.ba/1524124869

zbMATH Keywords

spatial statisticsreference priorhierarchical modelsobjective priorconditional autoregressive model

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Inference from spatial processes (62M30) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Bayesian inference (62F15)

Related Items (4)

Integrated nested Laplace approximation method for hierarchical Bayesian inference of spatial model with application to functional magnetic resonance imaging data ⋮ Fast and scalable computations for Gaussian hierarchical models with intrinsic conditional autoregressive spatial random effects ⋮ Objective Bayesian analysis for Gaussian hierarchical models with intrinsic conditional autoregressive priors ⋮ The limiting distribution of the Gibbs sampler for the intrinsic conditional autoregressive model

Uses Software

• spBayes
• BEAST
• CARBayes

Cites Work

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