Overview

Thursday, October 4

8:30 - 12:00       Short Course I:  Statistical Models and Methods for Spatial and Spatio-temporal Data with Strong Local Dependence 

Instructor: Professor Michael Stein, Department of Statistics, University of Chicago

1:30 -  5:00        Short Course II:  Introduction to Analysis of Extremes:  Univariate and Multivariate Cases

Instructor: Professor Dan Cooley, Department of Statistics, Colorado State University


Friday, October 5

8:15 - 8:30         Welcome 

      Brian Reich and Murali Haran 

8:30 - 10:30       Invited Session I: Spatial Extremes

Session chair: Dave Higdon

  • "Calibration of numerical model output using nonparametric spatial density functions" Montse Fuentes, Department of Statistics, North Carolina State University
  • "Statistical modeling of extreme value behavior in North American tree-ring density series" Elizabeth Mannshardt, Department of Statistics, North Carolina State University
  • "Attribution of Extreme Climatic Events" Richard Smith, Department of Statistics, University of North Carolina, Chapel Hill
  • "Bayesian spatial extreme value analysis to assess the changing risk of concurrent high temperatures across large portions of European cropland" Ben Shaby, Department of Statistics, University of California Berkeley
Invited Session I Abstracts

10:45 - 12:45     Invited Session II: Recent Methodological Developments in Spatial Statistics

Session chair: Petrutza Caragea

  • "Some Reflections on the Theoretical Study in Spatial Statistics" Hao Zhang, Department of Statistics, Purdue University 
  • "Analysis of Variance for Functional and Image Data, with Climate Applications" Marc Genton, Department of Statistics, Texas A&M University
  • "Nonparametric Estimation of Spatial Covariance Function" Bo Li, Department of Statistics, Purdue University
  • "Multivariate Receptor Models for Spatially Correlated Multi-Pollutant Data" Mikyoung Jun, Department of Statistics, Texas A&M University
Invited Session II Abstracts

2:30 - 4:30         Poster Session



Saturday, October 6

8:30 - 10:30       Invited Session III: Complex Computer Models

Session chair: Mikyoung Jun

  • "Exploring the magnetosphere: Parameter estimation for the LFM model" Steve Sain, National Center for Atmospheric Research, Colorado.
  • "Mining Spatial Structure in Regional Climate" Doug Nychka, National Center for Atmospheric Research, Colorado.
  • "A comparison of methods for estimating uncertainties in model parameters and model-based predictions" Dave Higdon, Los Alamos National Labs
  • "Blending and downscaling ensembles of climate model predictions" Bruno Sanso, Department of Statistics, University of California Santa Cruz.
Invited Session III Abstracts

10:45 - 12:45     Invited Session IV: High-Dimensional Spatial Data

      Session chair: Victor De Oliveira

  • "Efficient Time-Frequency Representations in High-Dimensional Spatial and Spatio-Temporal Models" Chris Wikle,Department of Statistics, University of Missouri
  • "Dimension Reduction and Alleviation of Confounding for Spatial GeneralizedLinear Mixed Models" John Hughes, Department of Biostatistics, University of Minnesota
  • "Hierarchical factor models for large spatially misaligned data: A low-rank predictive process approach" Sudipto Banerjee, Department of Biostatistics, University of Minnesota
  • "Estimation and prediction in spatial models with block composite likelihoods" Jo Eidsvik, Department of Mathematical Sciences, NTNU, Trondheim, Norway
Invited Session IV Abstracts

2:30 - 4:30         Invited Session V: Non-Gaussian Spatial Processes

Session chair: Bo Li

  • "Bayesian Probit Regression for Multicategory Spatial Data" Kate Calder, Department of Statistics, The Ohio State University
  • "On Properties of Hierarchical Poisson Models for Spatial Count Data" Victor De Oliveira, Department of Management Science and Statistics, University of Texas at San Antonio
  • "Multilevel Latent Gaussian Spatial Process Model for Mixed Discrete and Continuous Multivariate Response Data" Jennifer Hoeting, Department of Statistics, Colorado State University
  • "Analysis of Areal Data: Should a Model with (Spatial) Dependence be Considered?" Petrutza Caragea, Department of Statistics, Iowa State University
Invited Session V Abstracts

 
4:30 - 4:45         Vote of Thanks/Closing Remarks

      Brian Reich and Murali Haran