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Estimation of the multinomial logit model with random effects
Applied Economics Letters, 2003In the present paper, it is shown how to perform estimation of the random effects multinomial logit model in the SAS program. Inference in the random effects multinomial logit model is complicated because it requires evaluation of multi-dimensional integrals.
Svarer, M., Machow-Møller, N.
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A multilevel multinomial logit model for the analysis of graduates’ skills
Statistical Methods and Applications, 2006zbMATH Open Web Interface contents unavailable due to conflicting licenses.
GRILLI, LEONARDO, RAMPICHINI, CARLA
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Preferences-based learning of multinomial logit model
Knowledge and Information Systems, 2018We learn the parameters of the popular multinomial logit model to gain insights about a DM’s decision process. We accomplish this objective through the recent algorithmic advances in the emerging field of preference learning. The empirical evaluation of the proposed approach is performed on a set of 12 publicly available benchmark datasets.
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The Nested Multinomial Logit Model
1987An important and intuitive generalization of the MNL specification is the nested multinomial logit (NMNL) model (McFadden, 1978). This model is able to generate substantial deviations from the “Independence of Irrelevant Alternatives” assumption but retains most of the computational advantages of the MNL model. Because of these features, the NMNL model
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Integrating the Dirichlet-multinomial and multinomial logit models of brand choice
Marketing Letters, 1993This paper discusses the interpretative benefits that arise from merging the Dirichlet-multinomial (DM) model as a loyalty variable in the multinomial logit (MNL) model of brand choice. The estimated parameters of this hybrid model compare favorably to those of a “pure” DM model (with no marketing mix variables) as well as those of a standard MNL model
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Rules of thumb for comparing multinomial logit and multinomial probit coefficients
Economics Letters, 1989zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Learning Mixed Multinomial Logits with Provable Guarantees
SSRN Electronic Journal, 2022Yiqun Hu +2 more
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2004
Le modèle logit à coefficients aléatoires est le modèle le plus prometteur parmi les modèles de choix discrets. Il généralise le modèle logit multinomial standard et utilise des méthodes de simulation pour l'estimation du modèle. De plus, il permet d'estimer la distribution des propensions marginales à payer.
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Le modèle logit à coefficients aléatoires est le modèle le plus prometteur parmi les modèles de choix discrets. Il généralise le modèle logit multinomial standard et utilise des méthodes de simulation pour l'estimation du modèle. De plus, il permet d'estimer la distribution des propensions marginales à payer.
openaire +1 more source