Bayesian Inference in the Multinomial Logit Model

Authors

  • Sylvia Frühwirth-Schnatter University of Economics and Business, Vienna
  • Rudolf Frühwirth Austrian Academy of Sciences, Vienna

DOI:

https://doi.org/10.17713/ajs.v41i1.186

Abstract

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.

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Published

2016-02-24

How to Cite

Frühwirth-Schnatter, S., & Frühwirth, R. (2016). Bayesian Inference in the Multinomial Logit Model. Austrian Journal of Statistics, 41(1), 27–43. https://doi.org/10.17713/ajs.v41i1.186

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