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Wu, G., S.H. Holan, C.H. Nilon, and C.K. Wikle. "Bayesian Binomial Mixture Models for Estimating Abundance in Ecological Monitoring Studies." Annals of Applied Statistics 9 (2015): 1-26. DOI: 10.1214/14-AOAS801, available at http://projecteuclid.org/euclid.aoas/1430226082.
Wu, G., S.H. Holan, and C.K. Wikle. "Hierarchical Bayesian Spatio-Temporal Conway-Maxwell Poisson Models with Dynamic Dispersion." Journal of Agricultural, Biological, and Environmental Statistics 18 (2013): 335-356. DOI: 10.1007/s13253-013-0141-2, available at http://link.springer.com/article/10.1007/s13253-013-0141-2.
Wu, G.. "Bayesian Modeling in the Era of Big Data: the Role of High-Throughput and High-Performance Computing." In The Extreme Science and Engineering Discovery Environment Conference. San Diego, CA, 2013.
Wu, G.. "Binomial Mixture Models for Urban Ecological Monitoring Studies Using American Community Survey Demographic Covariates." In Joint Statistical Meetings 2013. Montreal, Canada, 2013.
Wu, G., and S.H. Holan. "Bayesian Hierarchical Multi-Population Multistate Jolly-Seber Models with Covariates: Application to the Pallid Sturgeon Population Assessment Program." Journal of the American Statistical Association 112, no. 518 (2017): 471-483. DOI: 10.1080/01621459.2016.1211531, available at http://www.tandfonline.com/doi/abs/10.1080/01621459.2016.1211531.
Woodruff, A., V. Pihur, A. Acquisti, S. Consolvo, L. Schmidt, and L. Brandimarte. "Would a Privacy Fundamentalist Sell their DNA for \$1000... if Nothing Bad Happened Thereafter? A Study of the Western Categories, Behavior Intentions, and Consequences." In Proceedings of the Tenth Symposium on Usable Privacy and Security (SOUPS). New York, NY: ACM, 2014, available at https://www.usenix.org/conference/soups2014/proceedings/presentation/woodruff.
Wilson, Courtney, and Daniel G. Brown. NCRN Meeting Fall 2014: Change in Visible Impervious Surface Area in Southeastern Michigan Before and After the "Great Recession". NCRN Coordinating Office Preprint 1813:37446, 2014, available at http://hdl.handle.net/1813/37446.
Wilson, C. R., and D. G. Brown. "Change in Visible Impervious Surface Area in Southeastern Michigan Before and After the “Great Recession:” Spatial Differentiation in Remotely Sensed Land-Cover Dynamics." Population and Environment 36, no. 3 (2015): 331-355. DOI: 10.1007/s11111-014-0219-y, available at http://link.springer.com/article/10.1007%2Fs11111-014-0219-y.
Wilson, C. R.. Using Satellite Imagery to Evaluate and Analyze Socioeconomic Changes Observed with Census Data. Ph.D., 2013.
Wildhaber, M.L., R. Dey, C.K. Wikle, C.J. Anderson, E.H. Moran, and K.J. Franz. "A stochastic bioenergetics model based approach to translating large river flow and temperature in to fish population responses: the pallid sturgeon example." Geological Society 408 (2015). DOI: 10.1144/SP408.10.
Wildhaber, M.L., C.K. Wikle, E.H. Moran, C.J. Anderson, K.J. Franz, and R. Dey. "Hierarchical, stochastic modeling across spatiotemporal scales of large river ecosystems and somatic growth in fish populations under various climate models: Missouri River sturgeon example." Geological Society (2015).
Wikle, C.K.. "Nonlinear Dynamic Spatio-Temporal Statistical Models." In Southern Regional Council on Statistics Summer Research Conference., 2013.
Wikle, C.K.. "Hierarchcial models for uncertainty quantification: An overview." In Handbook of Uncertainty Quantification, edited by Ghanem, R., Higdon, D. and Owhadi, H.. Springer, 2015.
Wikle, C.K.. "Ecological Prediction with Nonlinear Multivariate Time-Frequency Functional Data Models." In Joint Statistical Meetings 2013. Montreal, Canada, 2013.
Wikle, C.K.. Efficient Time-Frequency Representations in High-Dimensional Spatial and Spatio-Temporal Models., 2012.
Wikle, C.K., and S.H. Holan. "Comment on ``Semiparametric Bayesian Density Estimation with Disparate Data Sources: A Meta-Analysis of Global Childhood Undernutrition" by Finncane, M. M., Paciorek, C. J., Stevens, G. A., and Ezzati, M." Journal of the American Statistical Association (2015).
Wikle, C.K.. "Modern Perspectives on Statistics for Spatio-Temporal Data." WIRES Computational Statistics 7, no. 1 (2015): 86-98. DOI: 10.1002/wics.1341, available at http://dx.doi.org/10.1002/wics.1341.
Wikle, C.K.. Spatio-Temporal Statistics at Mizzou, Truman School of Public Affairs., 2012.
Wikle, C.K.. "Agent Based Models: Statistical Challenges and Opportunities." Statistics Views (2014), available at http://www.statisticsviews.com/details/feature/6354691/Agent-Based-Models-Statistical-Challenges-and-Opportunities.html.
Wikle, C., S. Holan, and N. Cressie. "Hierarchical Spatio-Temporal Models and Survey Research." Statistics Views (2013), available at http://www.statisticsviews.com/details/feature/4730991/Hierarchical-Spatio-Temporal-Models-and-Survey-Research.html.
Wikle, C.K.. "Hierarchical General Quadratic Nonlinear Models for Spatio-Temporal Dynamics." In Red Raider Conference. Lubbock, TX: Texas Tech University, 2012.
Wikle, C.K., and M.B. Hooten. "Hierarchical Agent-Based Spatio-Temporal Dynamic Models for Discrete Valued Data." In Handbook of Discrete-Valued Time Series, edited by R. Davis, S. Holan, R. Lund and N. Ravishanker. Boca Raton, FL.: Chapman and Hall/CRC Press, 2015, available at http://www.crcpress.com/product/isbn/9781466577732.
Wikle, Christopher K., Jonathan Bradley, and Scott Holan. NCRN Meeting Spring 2015: Regionalization of Multiscale Spatial Processes Using a Criterion for Spatial Aggregation Error. NCRN Coordinating Office Preprint 1813:40177, 2015, available at http://hdl.handle.net/1813/40177.
Wikle, C.K.. Statistics and the Environment: Overview and Challenges., 2013.
Wikle, C.K.. "Change of Support in Spatio-Temporal Dynamical Models." In Joint Statistical Meetings. Montreal, Canada, 2012.

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