Multinomial distribution, widely used in applications with discrete data, witnessed varieties of competing intervals from frequentist to Bayesian methods, still prove to be interesting in the case of zero counts or sparse contingency tables. The methods commonly recommended in both approaches are considered based on its influence of zero counts, polarizing cell counts, and aberrations. The infe...

We extend the multinomial logit model to represent some of the empirical phenomena that are frequently observed in the choices made by humans. These phenomena include the similarity effect, the attraction effect, and the compromise effect. We formally quantify the strength of these phenomena that can be represented by our choice model, which illuminates the flexibility of our choice model. We t...

The aim of this paper is to describe the structure of the household’s energy demand as a discretercontinuous choice and, on this basis, establish an econometric model suitable for the data available in the Norwegian Energy Sur̈ eys. The discrete appliance choice is Ž specified as a multinomial logit model, with a mixture of appliance attributes operating . Ž . costs and individual characteristic...

Estimation of disaggregate mode choice models to estimate the ridership share on a proposed new (or improved) intercity travel service and to identify the modes from which existing intercity travelers will be diverted to the new or upgraded service constitutes a critical part of evaluating alternative travel service proposals to alleviate intercity travel congestion. This paper develops a new h...

Generative Adversarial Networks (GAN) have limitations when the goal is to generate sequences of discrete elements. The reason for this is that samples from a distribution on discrete objects such as the multinomial are not differentiable with respect to the distribution parameters. This problem can be avoided by using the Gumbel-softmax distribution, which is a continuous approximation to a mu...