In statistics, a multinomial logit (MNL) model, also known as multinomial logistic regression, is a regression model which generalizes logistic regression by allowing more than two discrete outcomes.[1] That is, it is a model that is used to predict the probabilities of the different possible outcomes of a categorically distributed dependent variable, given a set of independent variables (which...

Several supervised learning algorithms are suited to classify instances into a multiclass value space. MultiNomial Logit (MNL) is recognized as a robust classifier and is commonly applied within the CRM (Customer Relationship Management) domain. Unfortunately, to date, it is unable to handle huge feature spaces typical of CRM applications. Hence, the analyst is forced to immerse himself into fe...

The random coefficients multinomial choice logit model, also known as the mixed logit, has been widely used in empirical choice analysis for the last thirty years. We prove that the distribution of random coefficients in the multinomial logit model is nonparametrically identified. Our approach requires variation in product characteristics only locally and does not rely on the special regressors...

Maximum entropy models are often used to describe supply and demand behavior in urban transportation and land use systems. However, they have been criticized for not representing behavioral rules of system agents and because their parameters seems to adjust only to modeler-imposed constraints. In response, it is demonstrated that the solution to the entropy maximization problem with linear cons...

The spatial model has been in use in political science for close to 30 years, and in that period it has achieved a place of prime importance as our paradigm of the process of candidatechoice used by voters. For much of this time political scientists have estimated models of candidatechoice using binary logit or probit, even in cases where there were more than two choices facing voters. Recently...

A semi-nonparametric generalized multinomial logit model, formulated using orthonormal Legendre polynomials to extend the standard Gumbel distribution, is presented in this paper. The resulting semi-nonparametric function can represent a probability density function for a large family of multimodal distributions. The model has a closed-form log-likelihood function that facilitates model estimat...

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. Zusammenfassung: Das multinomiale log...

the aim of this study was investigation of the factors affecting the primary choice of consumers in food purchasing in mashhad city by applying cross section data of 201 households in 2012. in this study, 56, 30, and 14% of the consumers chose healthiness of food, price of food, and taste of food, respectively, as the primary preference in food purchase. results of applying multinomial logit mo...