Smarter Than Your Average Model - Bayesian Model Averaging as a Spatial Analysis Tool (Short Paper)

Authors Chris Brunsdon , Paul Harris, Alexis Comber

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Author Details

Chris Brunsdon
  • National Centre for Geocomputation, Maynooth University, Ireland
Paul Harris
  • Rothamsted Research, Harpenden, UK
Alexis Comber
  • School of Geography, University of Leeds, UK

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Chris Brunsdon, Paul Harris, and Alexis Comber. Smarter Than Your Average Model - Bayesian Model Averaging as a Spatial Analysis Tool (Short Paper). In 12th International Conference on Geographic Information Science (GIScience 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 277, pp. 17:1-17:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)


Bayesian modelling averaging (BMA) allows the results of analysing competing data models to be combined, and the relative plausibility of the models to be assessed. Here, the potential to apply this approach to spatial statistical models is considered, using an example of spatially varying coefficient modelling applied to data from the 2016 UK referendum on leaving the EU.

Subject Classification

ACM Subject Classification
  • Mathematics of computing → Bayesian nonparametric models
  • Bayesian
  • Varying coefficient regression
  • Spatial statistics


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