Daly, A, Hess, S and Dekker, T (2014) Practical solutions for sampling alternatives in large-scale models. Transportation Research Record, 2429. 148 - 156. ISSN 0361-1981
Abstract
Many large-scale real-world transport applications have choice sets that are so large as to make model estimation and application computationally impractical. The ability to estimate models on subsets of the alternatives is thus of great appeal, and correction approaches have existed since the late 1970s for the simple multinomial logit (MNL) model. However, many of these models in practice rely on nested logit specifications, for example, in the context of the joint choice of mode and destination. Recent research has put forward solutions for such generalized extreme value (GEV) structures, but these structures remain difficult to apply in practice. This paper puts forward a simplification of the GEV method for use in computationally efficient implementations of nested logit. The good performance of this approach is illustrated with simulated data, and additional insights into sampling error are also provided with different sampling strategies for MNL.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | (c) 2014, National Academy of Sciences. This is an author produced version of a paper published in Transportation Research Record. Uploaded in accordance with the publisher's self-archiving policy |
Keywords: | Nested logit; sampling of alternatives; GEV; destination choice |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > Institute for Transport Studies (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 30 Mar 2015 10:47 |
Last Modified: | 19 Jan 2018 07:36 |
Published Version: | http://dx.doi.org/10.3141/2429-16 |
Status: | Published |
Publisher: | National Academy of Sciences |
Identification Number: | 10.3141/2429-16 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:84324 |