ABSTRACT: The multinomial logit model (MNL) has for many years provided the fundamental platform for the analysis of discrete choice. The basic model’s several shortcomings, most notably its inherent assumption of independence from irrelevant alternatives (IIA) have motivated researchers to develop a variety of alternative formulations. The mixed logit model stands as one of the most significant of these extensions. This paper proposes a semi-parametric extension of the MNL, based on the latent class formulation, which resembles the mixed logit model but which relaxes its requirement that the analyst makes specific assumptions about the distributions of parameters across individuals. An application of the model to the choice of long distanc...
A traditional discrete choice model assumes that an individual's decision-making process is bas...
Statisticians along with other scientists have made significant computational advances that enable t...
The nested logit model has been used extensively to model multi-dimensional choice situations. A dra...
The multinomial logit model (MNL) has for many years provided the fundamental platform for the analy...
The multinomial logit model in discrete choice analysis is widely used in transport research. It has...
This article applies two recently stated choice survey datasets of Japan to investigate the differen...
Representing unobserved heterogeneity or taste variations in behavioral choice analysis is receiving...
This article develops a new latent class (LC) model with a generalised nested logit (GNL) formulatio...
Latent class models offer an alternative perspective to the popular mixed logit form, replacing the ...
In Alberini et al. (this volume), an overview of the workhorse model (the Multinomial Logit, or MNL)...
The multinomial logit model in discrete choice analysis is widely used in transport research. It has...
A discrete choice model is presented that explicitly recognizes differences in the error structure a...
Statisticians along with other scientists have made significant computational advances that enable t...
A discrete choice model is presented that explicitly recognizes differences in the error structure a...
The multinomial logit model has been used widely as a fundamental tool for the analysis of discrete ...
A traditional discrete choice model assumes that an individual's decision-making process is bas...
Statisticians along with other scientists have made significant computational advances that enable t...
The nested logit model has been used extensively to model multi-dimensional choice situations. A dra...
The multinomial logit model (MNL) has for many years provided the fundamental platform for the analy...
The multinomial logit model in discrete choice analysis is widely used in transport research. It has...
This article applies two recently stated choice survey datasets of Japan to investigate the differen...
Representing unobserved heterogeneity or taste variations in behavioral choice analysis is receiving...
This article develops a new latent class (LC) model with a generalised nested logit (GNL) formulatio...
Latent class models offer an alternative perspective to the popular mixed logit form, replacing the ...
In Alberini et al. (this volume), an overview of the workhorse model (the Multinomial Logit, or MNL)...
The multinomial logit model in discrete choice analysis is widely used in transport research. It has...
A discrete choice model is presented that explicitly recognizes differences in the error structure a...
Statisticians along with other scientists have made significant computational advances that enable t...
A discrete choice model is presented that explicitly recognizes differences in the error structure a...
The multinomial logit model has been used widely as a fundamental tool for the analysis of discrete ...
A traditional discrete choice model assumes that an individual's decision-making process is bas...
Statisticians along with other scientists have made significant computational advances that enable t...
The nested logit model has been used extensively to model multi-dimensional choice situations. A dra...