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

Ke Wang, Xin Ye, Ram Pendyala, Yajie Zou

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

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.

Original languageEnglish (US)
Article numbere0186689
JournalPLoS One
Volume12
Issue number10
DOIs
StatePublished - Oct 1 2017

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logit analysis
travel
Logistic Models
Likelihood Functions
Switzerland
automobiles
Bicycles
Probability density function
Polynomials

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)

Cite this

On the development of a semi-nonparametric generalized multinomial logit model for travel-related choices. / Wang, Ke; Ye, Xin; Pendyala, Ram; Zou, Yajie.

In: PLoS One, Vol. 12, No. 10, e0186689, 01.10.2017.

Research output: Contribution to journalArticle

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