Modeling for Seasonal Marked Point Processes: An Analysis of Evolving Hurricane Occurrences

Athanasios Kottas

Statistics Department, Baskin School of Engineering, UC Santa Cruz

Seasonal point processes refer to stochastic models for random events which are only observed in a given season. We present a Bayesian nonparametric modeling approach to study the dynamic evolution of a seasonal marked point process intensity. The motivating application involves the analysis of hurricane landfalls along the U.S. Gulf and Atlantic coasts from 1900 to 2010, for which the focus will be on the evolution of the intensity for the process of hurricane landfall occurrences, and the respective maximum wind speed and associated damages.

Joint work with Sai Xiao and Bruno Sanso