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On the use of a Modified Latin Hypercube Sampling (MLHS) approach in the estimation of a Mixed Logit model for vehicle choice

Hess, S., Train, K.E. and Polak, J.W. (2006) On the use of a Modified Latin Hypercube Sampling (MLHS) approach in the estimation of a Mixed Logit model for vehicle choice. Transportation Research Part B: Methodological, 40 (2). pp. 147-163. ISSN 0191-2615

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Quasi-random number sequences have been used extensively for many years in the simulation of integrals that do not have a closed-form expression, such as Mixed Logit and Multinomial Probit choice probabilities. Halton sequences are one example of such quasi-random number sequences, and various types of Halton sequences, including standard, scrambled, and shuffled versions, have been proposed and tested in the context of travel demand modeling. In this paper, we propose an alternative to Halton sequences, based on an adapted version of Latin Hypercube Sampling. These alternative sequences, like scrambled and shuffled Halton sequences, avoid the undesirable correlation patterns that arise in standard Halton sequences. However, they are easier to create than scrambled or shuffled Halton sequences. They also provide more uniform coverage in each dimension than any of the Halton sequences. A detailed analysis, using a 16-dimensional Mixed Logit model for choice between alternative-fuelled vehicles in California, was conducted to compare the performance of the different types of draws. The analysis shows that, in this application, the Modified Latin Hypercube Sampling (MLHS) outperforms each type of Halton sequence. This greater accuracy combined with the greater simplicity make the MLHS method an appealing approach for simulation of travel demand models and simulation-based models in general.

Item Type: Article
Copyright, Publisher and Additional Information: Copyright © 2005 Elsevier Ltd. This is an author produced version of a paper published in 'Transportation Research Part B: Methodological'. Uploaded in accordance with the publisher's self-archiving policy.
Keywords: MLHS, Mixed Logit Model, vehicle, choice, estimation,
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Environment (Leeds) > Institute for Transport Studies (Leeds)
Depositing User: Mrs Cassie L. Dupras
Date Deposited: 03 Mar 2009 11:56
Last Modified: 06 Jun 2014 23:44
Published Version: http://dx.doi.org/10.1016/j.trb.2004.10.005
Status: Published
Publisher: Elsevier
Refereed: Yes
Identification Number: 10.1016/j.trb.2004.10.005
URI: http://eprints.whiterose.ac.uk/id/eprint/7925

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