- Stochastics Seminar
- Thursday, October 2, 2008 - 15:00 for 1 hour (actually 50 minutes)
- Skiles 269
- Mark Huber – Departments of Mathematics and Statistical Sciences, Duke University
Spatial data are often more dispersed than would be expected if the points were independently placed. Such data can be modeled with repulsive point processes, where the points appear as if they are repelling one another. Various models have been created to deal with this phenomenon. Matern created three algorithms that generate repulsive processes. Here, MatÃ©rn Type III processes are used to approximate the likelihood and posterior values for data. Perfect simulation methods are used to draw auxiliary variables for each spatial point that are part of the type III process.