Population growth, economic development, and rapid urbanization in many areas have led
to increased exposure and vulnerability of structural and infrastructure systems to hazards …

Gaining a better understanding of the factors that affect the likelihood of a vehicle crash has
been an area of research focus for many decades. However, in the absence of detailed …

Poisson regression is a popular tool for modeling count data and is applied in a vast array of
applications from the social to the physical sciences and beyond. Real data, however, are …

A major challenge in machine learning is the computational expense of training these
models. Model training can be viewed as a form of optimization used to fit a machine …

Large tropical cyclones cause severe damage to major cities along the United States Gulf
Coast annually. A diverse collection of engineering and statistical models are currently used …

Developed from the authors' graduate-level biostatistics course, Applied Categorical and
Count Data Analysis, Second Edition explains how to perform the statistical analysis of …

This study examines and analyzes marine accidents that have occurred over the past 20
years in the Black Sea. Geographic information system, human factor analysis and …

This paper documents the application of the Conway–Maxwell–Poisson (COM-Poisson)
generalized linear model (GLM) for modeling motor vehicle crashes. The COM-Poisson …

The Poisson distribution is a popular distribution for modeling count data, yet it is
constrained by its equidispersion assumption, making it less than ideal for modeling real …

Conway–Maxwell–Poisson (CMP) distributions are flexible generalizations of the Poisson
distribution for modelling overdispersed or underdispersed counts. The main hindrance to …