Bayesian Model Checking in Hierarchical Spatial Models for Count Data

• Activity Number: 424
• Type: Contributed
• Date/Time: Tuesday, August 2, 2011 : 2:00 PM to 3:50 PM
• Sponsor: Section on Bayesian Statistical Science
• Author(s): Liang Jing*+ and Victor De Oliveira
• Companies: The University of Texas at San Antonio and The University of Texas at San Antonio
• Keywords: model checking ; latent process ; incompatibility ; transformed residual

Abstract

Hierarchical spatial models for count data are increasingly used for data analysis in many earth sciences, but model checking and model selection in this class of models remain difficult tasks due to the presence of an unobservable latent process. For this class of models, we investigate the application of model checking methods based on measures of relative predictive surprise, as those described in Bayarri and Castellanos (2007). We also propose an alternative method to diagnose incompatibility between model and data based on a kind of transformed residuals. The usefulness of the proposed model checking methods is explored using both simulated and real spatial count data.