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Past Events

2014 Presentations

  1. “Bayesian Lattice Filters for Time-Varying Autoregression and Time-Frequency Analysis.” University of Maryland, Baltimore County; October 2014; Colorado School of Mines, Golden CO; November 2014 (S.H. Holan).
  2.  “Interaction-based parameterizations for nonlinear dynamic spatio-temporal models.” Department of Statistics, The Ohio State University, Columbus, OH; October 2014; Department of Statistics,Texas A&M, College Station, TX; October 2014 (C.K. Wikle).
  3. “Feature space reduction via dimension expansion of ‘big data’ time-series covariates.” Department of Statistics, The Pennsylvania State University, State College, PA; October 2014; Quantitative Psychology Department, University of Missouri, Columbia; November 2014 (C.K. Wikle).
  4.  “Regionalization of multiscale spatial processes using a criterion for spatial aggregation error,” Spatial Statistics Workshop, Texas A&M University; College Station, TX; January, 2015 (C.K. Wikle).
  5. "Spatio-temporal statistics in geodesign." Keynote speaker; Geodesign Summit, Esri; Redlands, CA; January 2015 (N. Cressie).
  6. "Statistical modelling of big, spatial, non-Gaussian data." Knibbs Lecture, Statistical Society of Australia Inc.; Canberra, Australia; November 2014 (N. Cressie).
  7. "Predictive inference for big, spatial, non-Gaussian data." Universite´ de Paris Ouest; Nanterre, France; December 2014 (N. Cressie).
  8.  “Mixed Effects Modeling for Areal Data that Exhibit Multivariate-Spatio-Temporal Dependencies.” NCRN Fall 2014 Meeting, New York, September 2014 (J.R. Bradley).
  9. “A Fully Bayesian Approach for Generating Synthetic Marks and Geographies for Confidential Data.” International Indian Statistical Association (IISA), Riverside CA, July 2014; New Researcher’s Conference, Boston, August 2014; Joint Statistical Meetings, Boston, August 2014; NCRN Fall 2014 Meeting, New York, September 2014 (H. Quick).
  10. “Survey Fusion for Data that Exhibit Multivariate, Spatio-Temporal Dependencies.” New Researcher’s Conference, Boston, August 2014 (J.R. Bradley).
  11. “The Poisson Change of Support Problem with Applications to the American Community Survey.” Joint Statistical Meetings, Boston, August 2014 (J.R. Bradley).
  12. “An Approach for Identifying and Predicting Economic Recessions in Real-Time Using Time-Frequency Models.” Joint Statistical Meetings, Boston, August 2014 (S.H. Holan).
  13. “JABES Showcase - Impact of Advanced Statistical Methods on Experiments and Studies in Agricultural and Environmental Sciences.” Invited Discussant, Joint Statistical Meetings, Boston, MA, August 2014 (S.H. Holan).
  14. “Spatio-Temporal Modeling of U.S. State-To-State Migration Flows.” Joint Statistical Meetings, Boston, MA, August 2014 (T. Oswald). 
  15. “Flexible Bayesian Methodology for Multivariate Spatial Small Area Estimation.” Joint Statistical Meetings, Boston, August 2014 (A. T. Porter).
  16. “Ecology of infectious disease.” Invited Discussion, SAMSI Program on Mathematical and Statistical Ecology: Opening Workshop, August 2014 (C.K. Wikle).
  17. “Statistics for Spatio-Temporal Data Tutorial.” Invited Tutorial Lecture, SAMSI Program on Mathematical and Statistical Ecology: Opening Workshop, August 2014 (C.K. Wikle).
  18. “ Evaluating epidemic and invasive species response to forcing from multivariate spatio-temporal response operators.” Joint Statistical Meetings, Boston, August 2014 (C.K. Wikle).
  19. “Bayesian Dynamic Time-Frequency Estimation.” Twelfth World Meeting of ISBA, Cancun, Mexico, July 2014, (S.H. Holan).
  20. “ Ecological prediction with high-frequency ``big data'' covariates. “ Plenary Lecture: International Statistical Ecology Conference, Montpellier, France, July, 2014 (C.K. Wikle).
  21. “Interaction-based parameterizations for nonlinear dynamic spatio-temporal statistical models.” Keynote Lecture: Twelfth World Meeting of ISBA, Cancun, Mexico, July 2014 (C.K. Wikle).
  22. “Hierarchical agent-based statistical models for spatio-temporal processes.” CIRES Bayesian Confab, University of Colorado, Boulder, CO, July 2014 (C.K. Wikle).
  23. “Feature space reduction via dimension expansion of high-dimensional functional covariates for prediction.” Invited seminar: The National Institute for Applied Statistics Research Australia, University of Wollongong, Australia, June, 2014 (C.K. Wikle).
  24.  “An Approach for Identifying and Predicting Economic Recessions in Real-Time Using Time-Frequency Functional Models,” Seminar on Bayesian Inference in Econometrics and Statistics (SBIES), University of Chicago Graduate School of Business, Chicago, May 2014 (S.H. Holan).
  25. “Prediction and design of spatially-dependent functional responses with spatially-dependent functional predictors for high-dimensional agricultural data.” Plenary Lecture: CSIRO “Looking in, Looking out: Agriculture and informatics, seeing and yielding the potential”, Cutting Edge Science Symposium, Adelaide, Australia, May, 2014 (C.K. Wikle).
  26. “Ecological Prediction with Nonlinear Multivariate Time-Frequency Functional Data Models,” University of Missouri, Department of Statistics, April 2014 (S.H. Holan).
  27. “A Bayesian Approach to Estimating Agricultural Yield Based on Multiple Repeated Surveys," U.S. Census Bureau -- Center for Statistical Research and Methodology (CSRM), March 2014 (S.H. Holan).
  28. “Bayesian Semiparameteric Hierarchical Empirical Likelihood Spatial Models.” The University of Nevada-Reno, January 2014; The Colorado School of Mines, February 2014; University of Wisconsin — Green Bay, February 2014; NCRN Virtual Seminar, May 2014 (A.T. Porter).
  29. “Spatial Fay-Herriot Models for Small Area Estimation With Functional Covariates," Computational Methods for Censuses and Surveys (SAMSI--Workshop), Washington D.C., January 2014 (S.H. Holan).
  30. “Big Data Methodology Applied to Small Area Estimation.” University of Colorado-Denver, January 2014 (A.T. Porter).
  31. “A Survey of Contemporary Spatial Models for Small Area Estimation.” Loyola University Chicago, January 2014 (A.T. Porter).
  32. “Bayesian Semiparameteric Hierarchical Empirical Likelihood Spatial Models.”  The University of Nevada-Reno, NV, January 2014; Colorado School of Mines, Golden, CO, February 2014; University of Wisconsin — Green Bay, February 2014 (A.T. Porter).