Spatial Microsimulation with R - Lovelace, Robin; Dumont, Morgane
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This is the first practical book on spatial microsimulation, an approach that involves the generation, analysis, and modeling of individual-level data allocated to geographical zones. Full of reproducible examples using code and data, the book demonstrates methods for population synthesis by combining individual and geographically aggregated datasets of administrative zones. This approach represents the "best of both worlds" in terms of spatial resolution and person-level detail, overcoming issues of data confidentiality and reproducibility.

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Produktbeschreibung
This is the first practical book on spatial microsimulation, an approach that involves the generation, analysis, and modeling of individual-level data allocated to geographical zones. Full of reproducible examples using code and data, the book demonstrates methods for population synthesis by combining individual and geographically aggregated datasets of administrative zones. This approach represents the "best of both worlds" in terms of spatial resolution and person-level detail, overcoming issues of data confidentiality and reproducibility.
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Autorenporträt
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.