TY - JOUR
T1 - Bayesian Inference in the Multinomial Logit Model
AU - Frühwirth-Schnatter, Sylvia
AU - Frühwirth, Rudolf
PY - 2012
Y1 - 2012
N2 - 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.
AB - 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.
UR - http://www.ajs.or.at/index.php/ajs/article/view/vol41%2C%20no1%20-%203
U2 - 10.17713/ajs.v41i1.186
DO - 10.17713/ajs.v41i1.186
M3 - Journal article
SN - 1026-597X
VL - 41
SP - 27
EP - 43
JO - Austrian Journal of Statistics
JF - Austrian Journal of Statistics
ER -