This article presents a detailed discussion and application of a methodology, called multinomial modeling, that can be used to measure and study cognitive processes. Multinomial modeling is a statistically based technique that involves estimating hypothetical parameters that represent the probabilities of unobservable cognitive events. Models in this class provide a statistical methodology that...

A Multinomial-Choice Model of Neighborhood Effects Author(s): William A. Brock and Steven N. Durlauf Source: The American Economic Review, Vol. 92, No. 2, Papers and Proceedings of the One Hundred Fourteenth Annual Meeting of the American Economic Association (May, 2002), pp. 298-303 Published by: American Economic Association Stable URL: http://www.jstor.org/stable/3083420 . Accessed: 10/09/20...

In-service training is education for employees to help them develop their professional skills in a specific discipline or occupation. This training takes place after an individual begins work responsibilities. On-line technology is supporting our learning in many ways. Both credit and degree pursuing are formal developing program. There is a need to developing a model of in-service training for...

Subspace multinomial model (SMM) is a log-linear model and can be used for learning low dimensional continuous representation for discrete data. SMM and its variants have been used for speaker verification based on prosodic features and phonotactic language recognition. In this paper, we propose a new variant of SMM that introduces sparsity and call the resulting model as `1 SMM. We show that `...

BACKGROUND It is of considerable interest to forecast the future burden of mesothelioma mortality. Data on deaths are available, whereas no measure of asbestos exposure is available. METHODS We compare two Poisson models: a response-only model with an age-cohort specification and a multinomial model with epidemiologically motivated frequencies. RESULTS The response-only model has 5% higher ...

Trial-offer markets, where customers can sample a product before deciding whether to buy it, are ubiquitous in the online experience. Their static and dynamic properties are often studied by assuming that consumers follow a multinomial logit model and try exactly one product. In this paper, we study how to generalize existing results to a more realistic setting where consumers can try multiple ...

This article introduces a model-based approach to distributed computing for multinomial logistic (softmax) regression. We treat counts for each response category as independent Poisson regressions via plug-in estimates for fixed effects shared across categories. The work is driven by the high-dimensional-response multinomial models that are used in analysis of a large number of random counts. O...

Log-multiplicative association models (LMA), which are special cases of log-linear models, have been derived as models for manifest probabilities based on multidimensional latent variables models for multi-category response data. Since discussion of between multiple derivations is lacking, we draw connections between multiple derivations with an emphasis on those pertaining to item response mod...

Random utility models often involve terms which represent alternative-specific errors, and the main attractive feature of the multinomial probit (MNP) model is that it allows a rather general covariance structure for these errors. However, since observed choices only reveal information regarding utility differences, and since scale cannot be determined, not all parameters in an arbitr~iry MNP s...