Beta-Binomial Kriging: An Alternative Model for Spatial Rates

• Activity Number: 247
• Type: Contributed
• Date/Time: Monday, August 10, 2015 : 2:00 PM to 3:50 PM
• Sponsor: Section on Statistics and the Environment
• Author(s): Aimee Schwab* and David Marx
• Companies: Xavier University and University of Nebraska - Lincoln
• Keywords: Beta-binomial ; Kriging ; Epidemiology ; Spatial prediction

Abstract

Recent innovations in spatial statistics have focused on the problem of non-normal data: specifically spatial counts and spatial proportions. A number of approaches have been proposed to model spatial proportions, including spatial GLMMs and Bayesian hierarchical models. While these approaches have their advantages, there is a serious jump in complexity over traditional spatial models which limits their use outside of statistics.

This paper will present an alternative approach called beta-binomial kriging. Inspired by Poisson kriging (Monestiez, 2006), beta-binomial kriging models latent beta spatial random fields as a function of observed sample proportions. Beta-binomial kriging is relatively simple compared to other models, and provides accurate predictions under a wide variety of circumstances. The approach is ideally suited for problems in epidemiology and spatial ecology where underlying probabilities of a phenomenon are of primary interest.