Bayesian Inference in the Multinomial Logit Model

Bayesian Inference in the Multinomial Logit Model

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 algorith...

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Veröffentlicht in:Österreichische Zeitschrift für Statistik 2016-02, Vol.41 (1)
Hauptverfasser: Frühwirth-Schnatter, Sylvia, Frühwirth, Rudolf
Format: Artikel
Sprache:eng
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Zusammenfassung: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.
ISSN:1026-597X
DOI:10.17713/ajs.v41i1.186