ABSTRACT A broad class of models that routinely appear in several fields can be expressed
as partially or fully discretized Gaussian linear regressions. Besides including classical …

Within the context of flexible parametric families of distributions, much work has been
dedicated in recent years to the theme of skew-symmetric distributions, or symmetry …

An intermediate-level treatment of Bayesian hierarchical models and their applications, this
book demonstrates the advantages of a Bayesian approach to data sets involving inferences …

We introduce a framework for estimating the effect that a binary treatment has on a binary
outcome in the presence of unobserved confounding. The methodology is applied to a case …

Class imbalance, where there are great differences between the number of observations
associated with particular discrete outcomes, is common within transportation and other …

The main purpose of this paper is to present an asymmetric logit probability model to
estimate and predict the daily probabilities of delay in aircraft arrivals. The proposed model …

We discuss some of the features of the R add-on package GJRM which implements a
flexible joint modeling framework for fitting a number of multivariate response regression …

A Bayesian inference approach using Markov Chain Monte Carlo (MCMC) is developed for
the logistic positive exponent (LPE) model proposed by Samejima and for a new skewed …

In binary regression, symmetric links such as logit and probit are usually considered as
standard. However, in the presence of unbalancing of ones and zeros, these links can be …

Among the discrete choice contexts discussed in the transportation literature, route choice is
particularly challenging, for which several model structures with different assumptions were …