The paper proposes a Bayesian multinomial logit model to analyse spatial patterns of urban expansion. specification assumes that the log-odds each class follow autoregressive proce...

We present a new multi-path routing methodology, MLBrouting, that is based on the multinomial logit model, which is well known in the random utility field. The key concept of the study is to set multiple paths from the origin to the destination, and distribute packets in accordance with multinomial logit type probability. Since MLB-routing is pure multi-path routing, it reduces the convergence ...

Recently, the Markov chain choice model has been introduced by Blanchet et al. to overcome the computational intractability for learning and revenue management for several modern choice models, including the mixed multinomial logit models. However, the known methods for learning the Markov models require almost all items to be offered in the learning stage, which is impractical. To address this...

mlogit is a package for R which enables the estimation the multinomial logit models with individual and/or alternative specific variables. The main extensions of the basic multinomial model (heteroscedastic, nested and random parameter models) are implemented.

mlogit is a package for R which enables the estimation of the multinomial logit models with individual and/or alternative specific variables. The main extensions of the basic multinomial model (heteroscedastic, nested and random parameter models) are implemented.

This paper discusses the representability of discrete logit-type models including multinomial logit and nested logit model from a mathematical approach. It is shown that the logit-type models can be reconstructed from mathematical approximation theory with sigmoidal functions widely used in Neural Network modeling without the basic assumptions such as IIA and iid, and the distribution (or densi...

This paper describes two Stata programs, mclgen and mclest, for imposing special restrictions on multinomial logistic models. MCL stands for Multinomial Conditional Logit, a term coined by Breen (1994). An MCL model uses a conditional logit program to estimate a multinomial logistic model. This produces the same log likelihood, estimates and standard errors, but allows greater flexibility in im...

This article proposes a method for multiclass classification problems using ensembles of multinomial logistic regression models. A multinomial logit model is used as a base classifier in ensembles from random partitions of predictors. The multinomial logit model can be applied to each mutually exclusive subset of the feature space without variable selection. By combining multiple models the pro...