Open AccessOn the development of a semi-nonparametric generalized multinomial logit model for travel-related choices
Author(s) -
Ke Wang,
Xin Ye,
Ram M. Pendyala,
Yajie Zou
Publication year - 2017
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0186689
Subject(s) - gumbel distribution , nonparametric statistics , multinomial logistic regression , multinomial distribution , econometrics , mixed logit , mathematics , generalized extreme value distribution , statistics , discrete choice , logit , function (biology) , logistic regression , extreme value theory , evolutionary biology , biology
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.