Two types of animal-vehicle collision (AVC) data are commonly adopted for AVC-related risk analysis research: reported AVC data and carcass removal data. One issue with these two data sets is that they were found to have significant discrepancies by previous studies. In order to model these two types of data together and provide a better understanding of highway AVCs, this study adopts a diagon...

In this paper we consider exact tests of a multiple logistic regression, where the levels of covariates are equally spaced, via Markov beses. In usual application of multiple logistic regression, the sample size is positive for each combination of levels of the covariates. In this case we do not need a whole Markov basis, which guarantees connectivity of all fibers. We first give an explicit Ma...

This article is concerned with the analysis of correlated count data, a class of model in which the correlation between the counts is presented by correlated unobserved heterogeneity components. A Hierarchical Bayesian analysis is used for estimation of the parameters. A Gibbs sampling algorithm is suggested for find posterior densities of parameters. The proposed method is applied to IVF data ...

The main purpose of this article is to present a new class bivariate mixed Poisson regression models with varying dispersion that offers sufficient flexibility for accommodating overdispersion and accounting the positive correlation between number claims from third-party liability bodily injury property damage. Maximum likelihood estimation family achieved through an expectation-maximization al...

The study introduces a distinction between two types of labor mobility: direct job to job changes (which are assumed to be voluntary) and job changes after experiencing an unemployment spell (assumed to be involuntary). Exploiting the close relationship between those two phenomena we adopt a bivariate regression framework for our empirical analysis of data on male individuals in the German labo...