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On the development of a semi-nonparametric generalized multinomial logit model for travel-related choices

A semi-nonparametric generalized multinomial logit model, formulated using orthonormal Legendre polynomials to extend the standard Gumbel distribution, is presented in this paper. The resulting semi-nonparametric function can represent a probability density function for a large family of multimodal...

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Detalles Bibliográficos
Autores principales: Wang, Ke, Ye, Xin, Pendyala, Ram M., Zou, Yajie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5658062/
https://www.ncbi.nlm.nih.gov/pubmed/29073152
http://dx.doi.org/10.1371/journal.pone.0186689
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author Wang, Ke
Ye, Xin
Pendyala, Ram M.
Zou, Yajie
author_facet Wang, Ke
Ye, Xin
Pendyala, Ram M.
Zou, Yajie
author_sort Wang, Ke
collection PubMed
description A semi-nonparametric generalized multinomial logit model, formulated using orthonormal Legendre polynomials to extend the standard Gumbel distribution, is presented in this paper. The resulting semi-nonparametric function can represent a probability density function for a large family of multimodal distributions. The model has a closed-form log-likelihood function that facilitates model estimation. The proposed method is applied to model commute mode choice among four alternatives (auto, transit, bicycle and walk) using travel behavior data from Argau, Switzerland. Comparisons between the multinomial logit model and the proposed semi-nonparametric model show that violations of the standard Gumbel distribution assumption lead to considerable inconsistency in parameter estimates and model inferences.
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spelling pubmed-56580622017-11-09 On the development of a semi-nonparametric generalized multinomial logit model for travel-related choices Wang, Ke Ye, Xin Pendyala, Ram M. Zou, Yajie PLoS One Research Article A semi-nonparametric generalized multinomial logit model, formulated using orthonormal Legendre polynomials to extend the standard Gumbel distribution, is presented in this paper. The resulting semi-nonparametric function can represent a probability density function for a large family of multimodal distributions. The model has a closed-form log-likelihood function that facilitates model estimation. The proposed method is applied to model commute mode choice among four alternatives (auto, transit, bicycle and walk) using travel behavior data from Argau, Switzerland. Comparisons between the multinomial logit model and the proposed semi-nonparametric model show that violations of the standard Gumbel distribution assumption lead to considerable inconsistency in parameter estimates and model inferences. Public Library of Science 2017-10-26 /pmc/articles/PMC5658062/ /pubmed/29073152 http://dx.doi.org/10.1371/journal.pone.0186689 Text en © 2017 Wang et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Wang, Ke
Ye, Xin
Pendyala, Ram M.
Zou, Yajie
On the development of a semi-nonparametric generalized multinomial logit model for travel-related choices
title On the development of a semi-nonparametric generalized multinomial logit model for travel-related choices
title_full On the development of a semi-nonparametric generalized multinomial logit model for travel-related choices
title_fullStr On the development of a semi-nonparametric generalized multinomial logit model for travel-related choices
title_full_unstemmed On the development of a semi-nonparametric generalized multinomial logit model for travel-related choices
title_short On the development of a semi-nonparametric generalized multinomial logit model for travel-related choices
title_sort on the development of a semi-nonparametric generalized multinomial logit model for travel-related choices
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5658062/
https://www.ncbi.nlm.nih.gov/pubmed/29073152
http://dx.doi.org/10.1371/journal.pone.0186689
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