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.
Identifer | oai:union.ndltd.org:VIENNA/oai:epub.wu-wien.ac.at:5629 |
Date | January 2012 |
Creators | Frühwirth-Schnatter, Sylvia, Frühwirth, Rudolf |
Publisher | Austrian Statistical Society |
Source Sets | Wirtschaftsuniversität Wien |
Language | English |
Detected Language | English |
Type | Article, PeerReviewed |
Format | application/pdf |
Rights | Creative Commons: Attribution 4.0 International (CC BY 4.0) |
Relation | http://www.ajs.or.at/index.php/ajs/article/view/vol41%2C%20no1%20-%203, http://www.ajs.or.at/index.php/ajs, http://www.ajs.or.at/index.php/ajs/about/editorialPolicies#openAccessPolicy, http://epub.wu.ac.at/5629/ |
Page generated in 0.0021 seconds