Department of Statistics
Iowa State University
Non-Stationary Spatial Models: Some Theory and Applications
In the past few decades significant advancements have been made in information technology and remote sensing hardware, making it much easier and less expansive to collect data from a wide range of spatial domains. As a result, there has been a tremendous growth of massive spatial datasets. In this talk I will introduce some flexible non-stationary spatial models and corresponding computationally efficient algorithms which can be used to analyze large spatial data. Some theoretical results on the estimation and plug-in prediction for non-stationary spatial models will be presented, and the total ozone data collected by TOMS (Total Ozone Mapping Spectrometer) will be analyzed as an illustration
Refreshments at 3:45pm in Snedecor 2101.