Synthetic spatial microdata enable analyses of artificial populations in the form of individual
unit record files at a small area level. They allow analyses of estimates of variables that are …

There has been a resurgence of interest in how the social, built and cultural environments
contribute to shaping health outcomes. The pathways relating place to health behaviour …

Geocomputation with R is for people who want to analyze, visualize and model geographic
data with open source software. It is based on R, a statistical programming language that …

There are several established methodologies for generating synthetic populations. These
include deterministic reweighting, conditional probability (Monte Carlo simulation) and …

Generate and Analyze Multi-Level Data Spatial microsimulation involves the generation,
analysis, and modeling of individual-level data allocated to geographical zones. Spatial …

The production of synthetic datasets has been proposed as a statistical disclosure control
solution to generate public use files out of protected data, and as a tool to create" …

Iterative proportional fitting (IPF) is a widely used method for spatial microsimulation. The
technique results in non-integer weights for individual rows of data. This is problematic for …

Synthetic population is used in many transport models ranging from trip-based, hybrid trip,
tour-based, and activity-based models. As mobility decisions depend on both individuals' …

In this chapter we introduce an approach to individual based modelling of social and
economic systems. Microsimulation models (MSM) appear similar to ABM through the …

Iterative Proportional Fitting (IPF), also known as biproportional fitting,'raking'or the RAS
algorithm, is an established procedure used in a variety of applications across the social …