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An efficient methodology for generating synthetic populations with multiple control levels

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Title: An efficient methodology for generating synthetic populations with multiple control levels
Alternative Title: Efficient methodology for generating synthetic populations with multiple control levels
Author(s): Auld, Joshua; Mohammadian, Abolfazl
Subject(s): population synthesis program multiple level synthetic populations
Abstract: 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
Issue Date: 2010
Publisher: National Academy of Science
Citation Info: Auld, J. & Mohammadian, A. 2010. Efficient Methodology for Generating Synthetic Populations with Multiple Control Levels. Transportation Research Record,(2175): 138-147. DOI: 10.3141/2175-16
Type: Article
Description: 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.
URI: http://hdl.handle.net/10027/7666
ISSN: 0361-1981
Sponsor: 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.
Date Available in INDIGO: 2011-05-25
 

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