The logit-mixed logit (LML) model is a very recent advancement in semiparametric discrete choice models. LML represents the mixing distribution of a logit kernel as a sieve function …
S Hess - Journal of Choice Modelling, 2010 - Elsevier
A number of authors have discussed the possible advantages of conditioning parameter distributions on observed choices when working with Mixed Multinomial Logit models …
J Swait - Journal of choice modelling, 2023 - Elsevier
When estimating random coefficients models from choice data, decisions relating to the multivariate density function assumed to describe preference heterogeneity across the …
The logit-mixed logit (LML) model, which allows the analyst to semi-parametrically specify the mixing distribution of preference heterogeneity, is a very recent advancement in logit …
The initial motivation leading to the results in this paper was a problem most choice modeling researchers may have not considered: how to simulate random disturbance terms …
The random coefficients, multinomial choice logit model has been widely used in empirical choice analysis for the last 30 years. We are the first to prove that the distribution of random …
The random coefficients multinomial choice logit model, also known as the mixed logit, has been widely used in empirical choice analysis for the last thirty years. We prove that the …
WH Greene, DA Hensher - Transportation Research Part E: Logistics and …, 2007 - Elsevier
Developments in simulation methods, and the computational power that is now available, have enabled open-form discrete choice models such as mixed logit to be estimated with …
Mixed logit models with unobserved inter-and intra-individual heterogeneity hierarchically extend standard mixed logit models by allowing tastes to vary randomly both across …