The analysis of discrete dyadic sequential behavior and, in particular, the problem of forecasting future behavior from current and past behavior in such data is the main theme of the present article. We propose to use multivariate multinomial logit models and the potential of which will be demonstrated with data on Imagery play therapy. In such a therapy, the therapist tries to draw a child in...

This study analyzed the factors affecting propensity internal migration of Indonesian elderly based on age classification elderly, i.e., young middle or old elderly. It used multinomial logit model that explored affect interaction between and external migration. was chosen beacuse dependent variable had polichotomous scale, nominal ordinal scale with more than two categories. The estimation res...

Maximum likelihood estimation of mixed effect baseline category logit models for multinomial longitudinal data can be prohibitive due to the integral dimension of the random effects distribution. We propose to use multidimensional unfolding methodology to reduce the dimensionality of the problem. As a by-product, readily interpretable graphical displays representing change are obtained. The met...

In this paper, we present a Weibull link (skewed) model for categorical response data arising from binomial as well as multinomial model. We show that, for such types of categorical data, the most commonly used models (logit, probit and complementary log–log) can be obtained as limiting cases. We further compare the proposed model with some other asymmetrical models. The Bayesian as well as fre...

An ex ante adoption model of bovine somatotropin (BST) is estimated with survey data of California milk producers. Theoretical justification is developed for incorporation of socioeconomic explanatory variables in a technology-adoption model. The advantages of a multinomial over a binomial ex ante model also are presented. The multinomial logit model is used to predict BST adoption, to test hyp...

We present the R package mnlogit for estimating multinomial logistic regression models, particularly those involving a large number of categories and variables. Compared to existing software, mnlogit offers speedups of 10–50 times for modestly sized problems and more than 100 times for larger problems. Running in parallel mode on a multicore machine gives up to 4 times additional speedup on 8 p...

In 2011, Lake Erie experienced a record-setting harmful algal bloom (HAB), posing significant risks to ecosystem services, including its $1.5 billion sport fishing industry. Using a mail survey of 3,000 Ohio recreational anglers and a choice experiment, this article provides the first empirical evidence in the US to link HABs to damages to Great Lakes recreational anglers. We account for the he...

Mode choice analysis has received the most attention among discrete choice problems in travel behavior literature. Most traditional mode choice models are based on the principle of random utility maximization derived from econometric theory. This paper investigates performance of mode choice analysis with classification methods decision trees, discriminant analysis and multinomial logit. Experi...

This paper deals with the correspondence between macro and micro spatial interaction and choice models, in both a static and a dynamic context. After a review of recent literature, special attention is devoted to the interpretation of aggregate spatial interaction models (both the conventional gravity or entropy models and the more general theory of movement devëloped by Alonso) in the framewor...

Assortment optimization problems arise widely in many practical applications such as retailing and online advertising. In this problem, the goal is to select a subset from a universe of substitutable items to offer to customers in order to maximize the expected revenue. The demand of any item depends on the substitution behavior of the customers that is captured mathematically by a choice model...