Traffic crashes present substantial challenges to human safety and socio-economic
development in urban areas. Developing a reliable and responsible traffic crash prediction …

Predicting traffic incident risks at granular spatiotemporal levels is challenging. The datasets
predominantly feature zero values, indicating no incidents, with sporadic high-risk values for …

Tweedie models can be used to analyze nonnegative continuous data with a probability
mass at zero. There have been wide applications in natural science, healthcare research …

In this paper we propose a statistical modeling framework that contributes to advancing
methods for modeling insurance policy premium in the actuarial literature. Specification of …

Double generalized linear models provide a flexible framework for modeling data by
allowing the mean and the dispersion to vary across observations. Common members of the …

In actuarial, ecological and political sciences, we often encounter data that are highly right-
skewed but have a spike at zero. To model such mixed types of data, Tweedie's compound …

In this dissertation we focus on developing a framework for detecting zones of rapid change
within a surface that is spatially or spatiotemporally indexed, which is termed as wombling …