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Beta-Binomial Kriging: A New Approach to Modeling Spatially Correlated Proportions
Abstract
Spatially correlated count data sets appear often in applied data analysis problems, but there is little consensus in the literature about how best to analyze the data. The two prevailing approaches provide accurate parameter estimates and predictions, at the cost of model interpretability and simplicity. This dissertation will present a new approach to modeling spatially correlated binomial observations: beta-binomial kriging. The model proposed here is a modified form of spatial kriging which assumes the data are generated from a correlated beta-binomial distribution. Given this assumption, the spatial parameters and predicted values can be estimated using simple matrix algebra. Beta-binomial kriging will be thoroughly assessed in the dissertation and shown to be a competitive option for modeling spatially correlated proportions. The model’s advantages will be illustrated using childhood vaccination rates.
Subject Area
Statistics
Recommended Citation
Schwab, Aimee D, "Beta-Binomial Kriging: A New Approach to Modeling Spatially Correlated Proportions" (2015). ETD collection for University of Nebraska-Lincoln. AAI3714259.
https://digitalcommons.unl.edu/dissertations/AAI3714259