University of Illinois at Chicago
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An efficient methodology for generating synthetic populations with multiple control levels

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journal contribution
posted on 2011-05-25, 00:00 authored by Joshua Auld, Abolfazl Mohammadian
This paper details a new methodology for controlling attributes on multiple analysis levels within a population synthesis program. The methodology determines how both household- and personlevel characteristics can jointly be used as controls when synthesizing populations, as well as how other multiple level synthetic populations, such as firm/employee, household/vehicle, etc. can be estimated. The use of multi-level controls is implemented through a new technique involving the estimation of household selection probabilities based on the probability of observing each household given the required person-level characteristics in each analysis zone. The new procedure is a quick and efficient method for generating synthetic populations which can accurately replicate desired person-level characteristics


The authors would like to acknowledge the financial support provided to this project from the Chicago Metropolitan Agency for Planning (CMAP) and the National Science Foundation (NSF) Integrative Graduate Education and Research Traineeship (IGERT) program in Computational Transportation Science at UIC.


Publisher Statement

Post print version of article may differ from published version. The definitive version is available through National Academy of Sciences at DOI: 10.3141/2175-16. © National Academy of Sciences. All Rights Reserved.


National Academy of Science


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