Data imputation in a short-run space-time series: A Bayesian approach

Lars Pforte, Chris Brunsdon, Conor Cahalane, Martin Charlton
2017 Environment and Planning B Urban Analytics and City Science  
This paper discusses a project on the completion of a database of socio-economic indicators across the European Union for the years from 1990 onward at various spatial scales. Thus the database consists of various time series with a spatial component. As a substantial amount of the data was missing a method of imputation was required to complete the database. A Markov Chain Monte Carlo approach was opted for. We describe the Markov Chain Monte Carlo method in detail. Furthermore, we explain how
more » ... we achieved spatial coherence between different time series and their observed and estimated data points.
doi:10.1177/0265813516688688 fatcat:wjpxinpuu5gyvdd4t47fkmkpha