Logit kernel is a discrete choice model that has both probit-like disturbances as well as an additive i.i.d. extreme value (or Gumbel) disturbance à la multinomial logit. The result is an intuitive, practical, and powerful model that combines the flexibility of probit with the tractability of logit. For this reason, logit kernel has been deemed the “model of the future” and is becoming extremel...

This paper reports on the results of a research carried out during 1993-94 aiming at studying street sellers as an informal sector activity and a source of socio-economic problems in Shiraz, Iran. This study makes use of two Logit models in order to present a unified framework depiciting the factors that seem to affect the developmeht of informal sector activities. The first model looks at thos...

One of the challenging issues for investors and professionals is appropriate models to evaluate financial situation of the firms. In this regard, many models have been extracted by researchers using different financial ratios to resolve these issues. However, choosing a model based on the conditions and users’ needs is complex. The main objective of this study is to identify the effect of conti...

Elimination by aspects (EBA) is a random utility model that is considered to represent the choice process used by consumers more faithfully than logit and probit models. One limitation of the model is that it does not have a known error theory. We show that EBA can be derived by assuming that aspects have random utilities with independent, extreme value distributions. Multinomial logit and rank...

The following research is guided by the hypothesis that products chosen on a shopping trip in a supermarket can indicate the preference interdependencies between different products or brands. The bundle chosen on the trip can be regarded as the result of a global utility function. More specifically: the existence of such a function implies a cross-category dependence of brand choice behavior. I...

In this paper, the performance of the Multi Dynamics Algorithm for Global Optimization (MAGO) is studied through simulation using five standard test functions. To guarantee that the algorithm converges to a global optimum, a set of experiments searching for the best combination between the only two MAGO parameters -number of iterations and number of potential solutions, are considered. These pa...

This article introduces a Markov chain Monte Carlo (MCMC) method for sampling the parameters of a multinomial logit model from their posterior distribution. Let yi ∈ {0, . . . ,M} denote the categorical response of subject i with covariates xi = (xi1, . . . , xip) T . Let X = (x1, . . . ,xn) T denote the design matrix, and let y = (y1, . . . , yn) T . Multinomial logit models relate yi to xi th...

We are focusing on three alternative techniques that can be used to empirically select predictors for failure prediction purposes. The selected techniques have all different assumptions about the relationships between the independent variables. Linear discriminant analysis is based on linear combination of independent variables, logit analysis uses the logistic cumulative probability function a...

Work zones are critical parts of the transportation infrastructure renewal process consisting of rehabilitation of roadways, maintenance, and utility work. Given the specific nature of a work zone (complex arrangements of traffic control devices and signs, narrow lanes, duration) a number of crashes occur with varying severities involving different vehicle sizes. In this paper we attempt to inv...