Choice probabilities of random utility maximization models when the errors distribution is a polynomial copula with Gumbel marginals
The expression of the choice probabilities of random utility maximization (RUM) models in which the utility errors distribution is a polynomial copula with Gumbel marginals is derived. In particular, it is shown that the expression of the Choice Probability Generating Function can be easily obtained from the polynomial copula of the distribution. This result is particularized for two types of polynomial copulas: the multivariate Farlie–Gumbel–Morgenstern copulas and the Baker's copulas. The correlation coefficient of the errors with these copulas is also obtained. The corresponding RUM models may account for relatively large negative and positive correlation. The RUM models introduced in this work are applied to two samples of interurban trips with three alternatives: airplane, rail and car. The results of the fit show that the models presented in this work may account for the correct correlation sign between the alternative errors and yield a better fit than a nested logit model.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/23249935
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Supplemental Notes:
- © 2020 Hong Kong Society for Transportation Studies Limited. Abstract reprinted with permission of Taylor & Francis.
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Authors:
- del Castillo, J M
- Publication Date: 2020-1
Language
- English
Media Info
- Media Type: Web
- Features: References;
- Pagination: pp 439-472
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Serial:
- Transportmetrica A: Transport Science
- Volume: 16
- Issue Number: 3
- Publisher: Taylor & Francis
- ISSN: 2324-9935
- EISSN: 2324-9943
- Serial URL: http://www.tandfonline.com/loi/ttra21
Subject/Index Terms
- TRT Terms: Air travel; Automobile travel; Choice models; Errors; Intercity travel; Logits; Railroad travel; Urban areas; Utility theory
- Subject Areas: Aviation; Highways; Planning and Forecasting; Railroads;
Filing Info
- Accession Number: 01761990
- Record Type: Publication
- Files: TRIS
- Created Date: Jan 6 2021 11:51AM