1977Transportation ScienceRequires access

Multinomial Probit and Qualitative Choice: A Computationally Efficient Algorithm

Carlos F. Daganzo, Fernando Bouthelier, Yosef Sheffi

Open publisher page 130 citations

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.

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What this paper is about

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.

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OpenAlex reports 130 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available 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.

Key concepts: Multinomial probit, Probit, Modal, Multinomial distribution, Multinomial logistic regression, Probit model, Computer science, Ordered probit

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