Spatio-temporal models for large-scale indicators of extreme weather

The changing global climate has sparked an interest in how these changes are affecting the intensity and frequency of extreme weather events such as thunderstorms and tornadoes because these extreme events pose a significant threat to life, property, and economic stability. This article uses and evaluates several spatio-temporal statistical extreme value models to model extreme weather from reanalysis data observed across the continental United States and Mexico. The models find that the intensity of extreme weather is particularly high for the central United States. Additionally, the intensity of extreme weather is increasing over time but the amount of increase may not be practically significant

Sports Ranking with Nonuniform Weighting

This paper introduces the integration of nonuniform weighting for sports ranking. While the ideas of the paper can be applied to any ranking method, a careful investigation is conducted on incorporating weighting in two of today's most popular ranking algorithms: the Colley and Massey methods, which were both developed for sports ranking applications and have since become the baseline standards there. The article introduces how to adapt both methods in order to weight some factors, such as late season play, home court advantage, or a winning streak, more heavily in computing the ratings of teams. To illustrate the utility of such weighting, the paper applies the algorithmic ideas in the area in which both Colley and Massey motivated their methods: sports. As such, the target application is producing brackets for the Division I NCAA Men's Basketball Tournament also known as March Madness. All the methods were used to produce brackets in the 2010 tournament and their results are given, including several mathematically-produced brackets that were better than 90 percent of the nearly 5 million brackets submitted to ESPN's Tournament Challenge.