On Wednesday April 17, 2013, Professor Noel Cressie of the University of Wollongong, Australia will present a one-day short course on Statistics for Spatio-Temporal Data at Census Bureau Headquarters. The course is co-sponsored by the Washington Statistical Society, and is free.
Attendees should have at least a Master's level background in probability and statistical inference, and they should have a good understanding of matrix algebra.
The course will follow the recently published book by Noel Cressie and Chris Wikle, "Statistics for Spatial Data" (Hoboken NJ: John Wiley and Sons, 2011). Professor Cressie will present state-of-the-art methods for spatio-temporal processes, bridging classic techniques with modern hierarchical statistical modeling concepts. 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 intoaccount. The course will consider a systematic approach to key quantitative techniques for the analysis of such data, particularly hierarchical (empirical and Bayesian) statistical modeling with an emphasis on dynamical spatio-temporal models. Illustrative real-world examples will be presented throughout the course. The course is split into four subsections:
- Overview of Statistical Modeling of Complex Data and Processes (key concepts of hierarchical modeling and overview of requisite background in spatial statistics and time series).
- Descriptive Analysis of Spatio-Temporal Data (exploratory techniques for spatio-temporal data including visualization and empirical dimension reduction).
- Fundamentals of Spatio-Temporal Modeling (spatio-temporal covariance functions, spatio-temporal kriging, relationship between process and covariance, and random-effects perspectives).
- Spatio-TemporalDynamical Models (hierarchical perspective of data, process, and parameter models for spatio-temporal dynamical systems; parameterization approaches for dealing with the curse of dimensionality;computation).
Noel Cressie, Ph.D., is Distinguished Professor, National Institute for Applied Statistics Research Australia, University of Wollongong, Australia. He has published extensively in the areas of statistical modeling, analysis of spatial and spatio-temporal data, and empirical-Bayesian and Bayesian methods. Dr. Cressie is a Fellow of the American Statistical Association and the Institute of Mathematical Statistics, and in 2009 he received the R.A. Fisher Lectureship, awarded by COPSS to recognize the importance of statistical methods for scientific investigations. He is the author of the 1993 book "Statistics for Spatial Data", revised edition, and co-author (with Chris Wikle) of the 2011 book, "Statistics for Spatio-Temporal Data".
This course is sponsored by the NSF-Census Bureau Research Network. Those who wish to attend should contact Sandra Heineck (sandra.l.heineck@census.gov) to reserve a place (up to 50 students can be accommodated). The course will start at 8:30 AM and conclude by 4:00 PM in Conference Room 4.