Statistics for Spatio-Temporal Data: New Challenges

• Activity Number: 97
• Type: Roundtables
• Date/Time: Monday, August 5, 2013 : 7:00 AM to 8:15 AM
• Sponsor: Section on Statistics and the Environment
• Author(s): Christopher K. Wikle*+
• Companies: University of Missouri
• Keywords: big data ; nonlinear ; spatial ; hierarchical ; environmental

Abstract

From understanding environmental processes and climate trends to developing new technologies for mapping public health data and the spread of invasive species, there is a high demand for statistical analyses of data that take spatial, temporal, and spatio-temporal information into account. The recently published book by Cressie and Wikle, "Statistics for Spatio-Temporal Data" (2011) , presents a systematic approach to quantitative techniques for the statistical analysis of such data. These methods feature statistical modeling with an emphasis on dynamical spatio-temporal models. Discussion will build on these ideas and focus on the utility of these methods with an emphasis on new challenges in spatio-temporal modeling. Some of these challenges include dimensionality, computation, incorporation of "big data," nonlinearity, and realistic measurement and sampling uncertainty.