Theatre B, Richard Berry Building
The University of Melbourne
Department of Mathematics & Statistics
University of Victoria., B.C.,
Canada
Data on incomes, wildfires, human settlements and oil fields indicate that these phenomena have very similar size distributions. Is there an underlying reason for the commonality? In this talk I will explore this question, by viewing each as an example of a stochastic process that is stopped (or `killed') in a random way. I will present some results on income distributions which provide an explanation and an extension of Pareto's Law of Incomes, and which lead to a new parametric income distribution model. This model can also explain Zipf's Law (or the rank-size law) for the sizes of cities, towns and villages. For forest fires and oil fields I will present results showing the excellent fit of a model derived from percolation theory.