Estimation and Inference for Massive Multivariate Spatial Data
Guinness will develop methods for investigating relationships among multiple variables observed within a spatial region, which will advance scientific understanding of physical processes and improve our ability to predict unobserved variables. The research will be applied to microscale chemistry experiments studying the behavior of toxic trace elements in soils, and to water and air quality monitoring data, with the aim of creating accurate maps of pollution levels in the the groundwater and atmosphere.