Multinomial Probit and Qualitative Choice: A Computationally Efficient Algorithm
Carlos F. Daganzo, Fernando Bouthelier, Yosef Sheffi
Abstract
Carlos F. Daganzo, Fernando Bouthelier, Yosef Sheffi
Abstract
Even though multinomial probit models have many attractive theoretical features and have been proposed for diverse choice problems (such as modal split and route choice in the transportation field), they have never been used in practice due to the lack of an adequate numerical technique for their application. The purpose of this paper is to introduce such a technique and to demonstrate the feasibility of forecasting with multinominal probit models. Our limited computational experience with the proposed numerical technique indicates that it is accurate, and can be efficiently applied to large choice problems.
OpenAlex reports 130 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
Even though multinomial probit models have many attractive theoretical features and have been proposed for diverse choice problems (such as modal split and route choice in the transportation field), they have never been used in practice due to the lack of an adequate numerical technique for their application. The purpose of this paper is to introduce such a technique and to demonstrate the feasibility of forecasting with multinominal probit models. Our limited computational experience with the proposed numerical technique indicates that it is accurate, and can be efficiently applied to large choice problems.
Key concepts: Multinomial probit, Probit, Modal, Multinomial distribution, Multinomial logistic regression, Probit model, Computer science, Ordered probit