Bayesian Inference in the Multinomial Logit Model
DOI:
https://doi.org/10.17713/ajs.v41i1.186Abstract
The multinomial logit model (MNL) possesses a latent variable representation in terms of random variables following a multivariate logistic distribution. Based on multivariate finite mixture approximations of the multivariate logistic distribution, various data-augmented Metropolis-Hastings algorithms are developed for a Bayesian inference of the MNL model.References
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