Functional logistic regression has been developed to forecast a binary response variable from a functional predictor. In order to fit this model, it is usual to assume that the functional observations and the parameter function of the model belong to a same finite space generated by a basis of functions. This consideration turns the functional model into a multiple logit model whose design matr...

The so-called “mixed” or “heterogeneous” multinomial logit (MIXL) model has become popular in a number of fields, especially Marketing, Health Economics and Industrial Organization. In most applications of the model, the vector of consumer utility weights on product attributes is assumed to have a multivariate normal (MVN) distribution in the population. Thus, some consumers care more about som...

This is an investigation of stochastic choice when only the average of the choices is observable. For example when one observes aggregate sales numbers from a store, but not the frequency with which each item was purchased. The focus of our work is on the Luce model, also known as the Logit model. We show that a simple path independence property of average choice uniquely characterizes the Luce...

As shown by Guimaraes, Figueiredo and Woodward (2003), a particular class of conditional logit models yield identical parameter estimates to a Poisson count data model. In Schmidheiny and Brülhart (2011), we have pointed out that the conditional logit model and the Poisson model can be seen as polar cases of a continuum of intermediate cases which emerge from a random utility nested logit model...

Categorical outcome (or discrete outcome or qualitative response) regression models are models for a discrete dependent variable recording in which of two or more categories an outcome of interest lies. For binary data (two categories) probit and logit models or semiparametric methods are used. For multinomial data (more than two categories) that are unordered, common models are multinomial and...

We compare and contrast two popular dynamic flexible functional forms for cost functions, the translog and the logit (Considine, 1990), using data on US industrial energy demand from 1960 to 1992 which has been analyzed by previous studies (Considine (1989) and Jones (1995)). We show the crucial role played by different dynamic formulations of the translog in this analysis of factor demands wit...

Chaos theory has recently caught the attention in the social sciences for its capability of capturing irregular motions which are endogenously produced in economie and social systems. However, in many cases major questions are arising concerning the real-world significance of critical parameter values leading to chaos, the testability of the models concerned and the validity of model specificat...

The main objective of a financial distress prediction model is to generate early warning signals.In this paper, we compare five bankruptcy prediction models, logit ,ANN ,CART, C5.0 and GP decision tree. Our empirical results reveal that the GP decision tree can outperform all the classifiers either in overall percentage of correct or k-fold cross validation test in out-sample. That is to say, G...

This paper develops an air passenger model that deals with city-pair demand generation and demand assignment in a single framework. Using publicly available and regularly collected panel data, the model captures both time series and cross-sectional variation of air travel demand. The empirical analysis finds that pattern of correlations among alternatives can be described by a three-level neste...