This study aims to evaluate the impact of pavement physical characteristics on the frequency of single-vehicle run-off-road (ROR) crashes in two-lane separated rural highways. In order to achieve this goal and to introduce the most accurate crash prediction model (CPM), authors have tried to develop generalized linear models, including the Poisson regression (PR), negative binomial regression (...

An m-sample semiparametric model in which the ratio of m − 1 probability density functions with respect to the mth is of a known parametric form without reference to any parametric model is considered. This model arises naturally from retrospective studies and multinomial logistic regression model. A projection density estimator is constructed by smoothing the increments of the maximum semipara...

Given the well known convergence difficulties in fitting log binomial regression with standard GLM software, we implement a direct solution via constrained optimization which avoids the circumventions found in the literature. The use of a log binomial model is motivated by our interest in directly estimating relative risks adjusted for confounders. A Bayesian log binomial regression model is al...

We consider the Bayesian analysis of outlier models. We show that the Gibbs sampler brings considerable conceptual and computational simplicity to the problem of calculating posterior marginals. Although other techniques for finding posterior marginals are available, the Gibbs sampling approach is notable for its ease of implementation. Allowing the probability of an outlier to he unknown intro...