Welcome to the National Transport Library Catalogue

Normal view MARC view

Efficient Methodology for Generating Synthetic Populations with Multiple Control Levels Auld, Joshua ; Mohammadian, Abolfazl

By: Contributor(s): Series: Transportation Research Record: Journal of the Transportation Research Board ; 2175Publication details: Washington DC Transportation Research Board, 2010Description: s. 138-147ISBN:
  • 9780309160513
Subject(s): Bibl.nr: VTI P8167:2175Location: TRBAbstract: This paper details a new methodology for controlling attributes on multiple analysis levels in a population synthesis program. The methodology determines how household- and person-level characteristics can jointly be used as controls when populations are synthesized as well as how other multiple-level synthetic populations, such as firm and employee or household and vehicle, can be estimated. The use of multilevel controls is implemented through a new technique involving the estimation of household selection probabilities on the basis of 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 that can accurately replicate desired person-level characteristics.
Item type: Reports, conferences, monographs
Holdings
Cover image Item type Current library Home library Collection Shelving location Call number Materials specified Vol info URL Copy number Status Notes Date due Barcode Item holds Item hold queue priority Course reserves
Statens väg- och transportforskningsinstitut Available

This paper details a new methodology for controlling attributes on multiple analysis levels in a population synthesis program. The methodology determines how household- and person-level characteristics can jointly be used as controls when populations are synthesized as well as how other multiple-level synthetic populations, such as firm and employee or household and vehicle, can be estimated. The use of multilevel controls is implemented through a new technique involving the estimation of household selection probabilities on the basis of 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 that can accurately replicate desired person-level characteristics.