The principal investigator will develop inferential techniques for problems where it is thought the spatial locations of the data are an important component of the assumed stochastic model. Three specific problems are considered: (1) spatial prediction and regional mapping, (2) modeling and inference for (marked) point processes, and (3) tumor-growth modeling based on random sets. Both theoretical and applied statistical issues are addressed: new spatial stochastic models will be built, parameter estimators will be developed, inference results for those estimators will be proved, and scientific applications on real data will be featured. This work will have impact on various fields such as earth sciences, geography, oceanography, hydrology, and environmetrics.
