University of California, Los Angeles - Department of Statistics
This talk will review some ways of transforming point processes, including smoothing, thinning, superposition, rescaling, and tessellation. Ways in which each of these may be used in the analysis of point process data will be examined, especially in relation to the problem of estimating wildfire hazard. We will explore in particular an important computational geometry problem involving tessellations, namely the estimation of point locations from piecewise constant image data via Dirichlet tessellation inversion.
No background knowledge is required whatsoever - only an interest in spatial problems, environmental data, and/or geometry.