Spatial Microsimulation with R

Robin Lovelace is a University Academic Fellow at the University of Leeds specializing in methods of spatial data analysis and applied transport modeling. Creator of the stplanr package and a number of popular tutorials, he is an experienced R user, teacher, and developer. Robin uses open source software daily for spatial analysis, map making, statistics, and modeling. His current research focuses on online interactive mapping and modeling to provide the evidence base needed for a transition away from fossil fuels in the transport sector. Morgane Dumont is an applied mathematician currently undertaking a PhD at the University of Namur. She has a wealth of experience programming in R, Python, C, Fortran, and MATLAB®. Her research focuses on forecasting the health needs of the elderly in 2030 for Belgium. To achieve this aim, Morgane is developing a synthetic population for Belgium as an input to an agent-based model.

Introducing spatial microsimulation with R. Introduction. SimpleWorld: A worked example of spatial microsimulation. What is spatial microsimulation? Generating spatial microdata. Data preparation. Population synthesis. Alternative approaches to population synthesis. Spatial microsimulation in the wild. Model checking and evaluation. Population synthesis without microdata. Household allocation. Modelling spatial microdata. The TRESIS approach to spatial microsimulation. Spatial microsimulation for agent-based models. Appendix. Glossary. Bibliography.