Objective Bayesian analysis of spatial models with separable correlation functions

DOI10.1002/cjs.11186zbMath1273.62032OpenAlexW2162668636MaRDI QIDQ2851581

Cuirong Ren, Sujit K. Sahu, Dongchu Sun

Publication date: 11 October 2013

Published in: Canadian Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/cjs.11186

zbMATH Keywords

geostatisticsreference priorJeffreys priorintegrated likelihoodpropriety of posterior

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Linear regression; mixed models (62J05) Measures of association (correlation, canonical correlation, etc.) (62H20) Bayesian inference (62F15) Bayesian problems; characterization of Bayes procedures (62C10) Geostatistics (86A32)

Related Items (3)

Robust Gaussian stochastic process emulation ⋮ Optimal compromise between incompatible conditional probability distributions, with application to Objective Bayesian Kriging ⋮ Propriety of the reference posterior distribution in Gaussian process modeling

Uses Software

• spBayes

Cites Work

• Unnamed Item
• Objective Bayesian analysis for a spatial model with nugget effects
• Interpolation with uncertain spatial covariances: A Bayesian alternative to Kriging
• Design and analysis of computer experiments. With comments and a rejoinder by the authors
• Default priors for Gaussioan processes
• A note of the approximation of likelihood function for a spatial model
• Objective Bayesian Analysis of Spatially Correlated Data
• Bayesian inference for variance components using only error contrasts
• Inequalities: theory of majorization and its applications

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