The multinomial probit (MNP) model is a popular tool for analyzing choice behavior as it allows correlation between alternatives. Because current specifications employ full covariance matrix of the latent utilities alternatives, they are not scalable to large number This article proposes factor structure on matrix, which makes sets. main challenge in estimating this that parameters require iden...

In the current paper, we propose a new utility-consistent modeling framework to explicitly link a count data model with an event type multinomial choice model. The proposed framework uses a multinomial probit kernel for the event type choice model and introduces unobserved heterogeneity in both the count and discrete choice components. Additionally, this paper establishes important new results ...

A mixed-effects multinomial logistic regression model is described for analysis of clustered or longitudinal nominal or ordinal response data. The model is parameterized to allow flexibility in the choice of contrasts used to represent comparisons across the response categories. Estimation is achieved using a maximum marginal likelihood (MML) solution that uses quadrature to numerically integra...

In contrast to the classical discrete choice experiment, the respondent in a rank-order discrete choice experiment, is asked to rank a number of alternatives instead of the preferred one. In this paper, we study the information matrix of a rank order nested multinomial logit model (RO.NMNL) and introduce local D-optimality criterion, then we obtain Locally D-optimal design for RO.NMNL models in...

We describe experiments with a Naive Bayes text classifier in the context of anti-spam E-mail filtering, using two different statistical event models: a multi-variate Bernoulli model and a multinomial model. We introduce a family of feature ranking functions for feature selection in the multinomial event model that take account of the word frequency information. We present evaluation results on...

The goal of this study is to identify the risk factors of type II diabetes (T2D) in Al Madinah in the Kingdom of Saudi Arabia (KSA). Data were collected from the Primary Health Care Center (PHCC) of Al Madinah, KSA, from 2009 to 2014. The data are grouped or summarized, where the patients have different types of diabetes. The dependent variable is the type of T2D, and the independent variables ...

To make driving assistance system more humanized, this study focused on the prediction and assistance of drivers' perception-response time on mountain highway curves. Field tests were conducted to collect real-time driving data and driver vision information. A driver-vision lane model quantified curve elements in drivers' vision. A multinomial log-linear model was established to predict percept...

3 Model Specification 5 3.1 Binary choice . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 3.1.1 The binary probit model . . . . . . . . . . . . . . . . . . 6 3.1.2 The binary logit model . . . . . . . . . . . . . . . . . . . 7 3.2 More than two choices . . . . . . . . . . . . . . . . . . . . . . . 8 3.2.1 The multinomial probit model . . . . . . . . . . . . . . . 8 3.2.2 The multinomi...

Abstract-A discrete choice model is presented that explicitly recognizes differences in the error structure associated with a single “oddball” alternative within the choice set that has properties not common to the other alternatives. The model purportedly resolves questions related to the use of alternative-specific variables in transportation choice models to capture the effects of attributes...