E-prints
2017
- Bradley, J.R., Holan, S.H., and Wikle, C.K. (2017). Computationally Efficient Multivariate Spatio-Temporal Models for High-Dimensional Count-Valued Data. (With Discussion). To Appear - Bayesian Analysis.
- Bradley, J.R., Wikle, C.K., and Holan, S.H. (2017). Regionalization of Multiscale Spatial Processes using a Criterion for Spatial Aggregation Error. Journal of the Royal Statistical Society -- Series B. 79, 815-832.
- Holan, S.H., McElroy, T.S., and Wu, G. (2017). The Cepstral Model for Multivariate Time Series: The Vector Exponential Model, Statistica Sinica. 27, 23-42.
- Linero, A.R., Bradley, J.R., and Desai, A . (2017). Multi-rubric Models for Ordinal Spatial Data with Application to Online Ratings from Yelp.
- Lucchesi, L.R., and Wikle, C.K., (2017). Visualizing uncertainty in areal data estimates with bivariate choropleth maps, map pixelation, and glyph rotation. STAT. 6, 292-302.
- McDermott, P.L., and Wikle, C.K. (2017). An ensemble quadratic echo state network for nonlinear spatio-temporal forecasting. STAT, in press.
- Schliep, E.M., A.E. Gelfand, J.S. Clark, B.J. Tomasek (2017). Biomass prediction using density dependent diameter distribution models. Annals of Applied Statistics. In press.
- Simpson, M., Wikle, C.K., and Holan, S.H. (2017). Adaptively-Tuned Particle Swarm Optimization with Application to Spatial Design. STAT, 6, 145-159.
- Weinberg, D., et al. (16 co-authors, including Cressie, N., Holan, S.H., and Wikle, C.K.) (2017). Effects of a government-academic partnership: Has the NSF-Census Bureau Research Network helped secure the future of the Federal Statistical System? In preparation.
- Wu, G, Holan, S.H., Avril, A., and Waldström, J. (2017). A Bayesian Semiparametric Jolly-Seber Model with Individual Heterogeneity: An Application to Migratory Mallards at Stopover. Submitted.
- Wu, G. and Holan, S.H. (2017). Bayesian Hierarchical Multi-Population Multistate Jolly-Seber Models with Covariates: Application to the Pallid Sturgeon Population Assessment Program, Journal of the American Statistical Association. 518, 471--483.
2016
- Bradley, J.R., Holan, S.H., and Wikle, C.K. (2016). Bayesian Hierarchical Models with Conjugate Full-Conditional Distributions for Dependent Data from the Natural Exponential Family. Under Invited Revision - Journal of the American Statistical Association - T&M.
- Bradley, J.R., Wikle, C.K., and Holan, S.H. (2016). Bayesian Spatial Change of Support for Count-Valued Survey Data with Application to the American Community Survey. Journal of the American Statistical Association. 111, 472-487.
- Bradley, J.R., Wikle, C.K., and Holan, S.H. (2016). Hierarchical Models for Spatial Data with Errors that are Correlated with the Latent Process. Under Invited Revision -Statistica Sinica.
- Bradley, J.R., Cressie, N., and Shi, T. (2016). A Comparison of Spatial Predictors when Datasets Could be Very Large. Statistics Surveys, 10, 100-131.
- Bradley, J.R., Holan, S.H., and Wikle, C.K. (2016). Multivariate Spatio-Temporal Survey Fusion with Application to the American Community Survey and Local Area Unemployment Statistics. STAT, 5: 224 - 233.
- Cressie, N. and Zammit-Mangion, A. (2016) Multivariate Spatial Covariance Models: A Conditional Approach. Biometrika, 103.4, 915-935.
- Holan, S.H. and Wikle, C.K. (2016). Hierarchical Dynamic Generalized Linear Mixed Models for Discrete--Valued Spatio-Temporal Data. Handbook of Discrete--Valued Time Series. Richard A. Davis, Scott H. Holan, Robert Lund, and Nalini Ravishanker (Eds.). 327--348, Chapman & Hall/CRC.
- Lund, R., Holan, S.H., and Livsey, J. (2016). Long Memory Discrete--Valued Time Series. Handbook of Discrete--Valued Time Series, Richard A. Davis, Scott H. Holan, Robert Lund, and Nalini Ravishanker (Eds.). 447-458, Chapman & Hall/CRC.
- McElroy, T.S. and Holan, S.H. (2016). Computation of the Autocovariances for Time Series with Multiple Long-Range Persistencies. Computational Statistics and Data Analysis, 101: 44 - 56.
- Quick, H., Holan, S.H., and Wikle, C.K. (2016). Generating Partially Synthetic Geocoded Public Use Data with Decreased Disclosure Risk Using Differential Smoothing. Under Invited Revision -- Journal of the Royal Statistical Society - Series A.
- Yang, W.H., Holan, S.H., and Wikle, C.K. (2016). Bayesian Lattice Filters for Time-Varying Autoregression and Time-Frequency Analysis. Bayesian Analysis. 11, 977-1003.
2015
- Cressie, N. and Burden, S. (2015). Evaluation of diagnostics for hierarchical spatial statistical models. Geometry Driven Statistics. Wiley. Chichester, UK. 241-259.
- Cressie, N. and Chambers, R.L. (2015). Comment: Spatial sampling designs depend as much on "how much?" and "why?" as on "where?" [Comment on "Optimal design in geostatistics under preferential sampling" by G. da Silva Ferreira and D. Gamerman.] Bayesian Analysis. 10, 741-748.
- Cressie, N. and Zammit-Mangion, A. (2015). Multivariate Spatial Covariance Models: A Conditional Approach. arXiv preprint: 1504.01865.
- Cressie, N. and Burden, S. (2015). Figures of Merit for Simultaneous Inference and Comparisons in Simulation Experiments. STAT, 1: 196 - 211.
- Bradley, J.R., Cressie, N., and Shi, T. (2015). Comparing and Selecting Spatial Predictors Using Local Criteria (with discussion). Test, 24: 1-28. (Rejoinder: 2015, Vol. 24, pp. 54-60.)
- Bradley, J.R., Holan, S.H., and Wikle, C.K. (2015) Multivariate Spatio-Temporal Models for High-Dimensional Areal Data with Application to Longitudinal Employer-Household Dynamics. Annals of Applied Statistics. 9, 1761 – 1791.
- Bradley, J.R., Wikle, C.K., and Holan, S.H. (2015) Multiscale Analysis of Survey Data: Recent Developments and Exciting Prospects. Statistic Views, Wiley.
- Bradley, J.R., Wikle, C.K., and Holan, S.H. (2015) Spatio-Temporal Change of Support with Application to American Community Survey Multi-Year Period Estimates. STAT. 4, 255 – 270.
- Burden, S., Cressie, N., and Steel, D.G. (2015) The SAR Model for Very Large Datasets: A Reduced Rank Approach. Econometrics. 3, 317 – 338.
- Cressie, N. and Chambers, R.L. (2015) Comment on Article by Ferreira and Gammerman. Bayesian Analysis. 10, 741 – 748.
- Porter, A.T., Holan, S.H., and Wikle, C.K. (2015) Bayesian Semiparametric Hierarchical Empirical Likelihood Spatial Models. Journal of Statistical Planning and Inference, 165, 78 – 90.
- Porter, A.T., Wikle, C.K., and Holan, S.H. (2015) Small Area Estimation via Multivariate Fay-Herriot Models with Latent Spatial Dependence. Australian & New Zealand Journal of Statistics. 57, 15 – 29.
- Porter, A.T., Holan, S.H., and Wikle, C.K. (2015) Multivariate Spatial Hierarchical Bayesian Empirical Likelihood Methods for Small Area Estimation. STAT, 4: 108 – 116.
- Quick, H., Holan, S.H., Wikle, C.K., and Reiter, J.P. (2015). Bayesian Marked Point Process Modeling for Generating Fully Synthetic Public Use Data with Point-Referenced Geography. Spatial Statistics, 14: 439 - 451.
- Quick, H, Holan, S.H., and Wikle, C.K. (2015) Zeros and Ones: A Case for Suppressing Zeros in Sensitive Count Data with an Application to Stroke Mortality. STAT, 4, 227 – 234.
- Quick, H., Holan, S.H., Wikle, C.K., and Reiter, J.P. (2015) Bayesian Marked Point Process Modeling for Generating Fully synthetic Public Use Data with Point-Referenced Geography. Spatial Statistics, 14, 439 – 451.
- Ryan, M, Bradley, J.R., Oswald, T, Wikle, C.K., and Holan, S.H. (2015) An Analysis of Bullying and Suicide in the United States using a Non-Gaussian Multivariate Spatial Model. Proceedings of The National Conference On Undergraduate Research (NCUR). Eastern Washington University, Cheney, WA.
2014
- McElroy, T.S. and Holan, S.H. (2014) Asymptotic Theory of Cepstral Random Fields. Annals of Statistics. 4, 64 – 86.
- McElroy, T.S. and Holan, S.H. (2014) Fast Estimation of Time Series with Multiple Long-Range Persistencies, ASA Proceedings of the Joint Statistical Meetings, American Statistical Association (Alexandria, VA).
- Porter, A.T., Holan, S.H., Wikle, C.K., and Cressie, N. (2014) Spatial Fay-Herriot Models for Small Area Estimation with Functional Covariates. Spatial Statistics. 10, 27 – 42.
- Porter, A.T. and Oleson, J. (2014) A CAR Model for Multiple Outcomes on Mismatched Lattices. Spatial and Spatio-Temporal Epidemiology. 11, 79 – 88.
- Wikle, C.K. (2014) Agent Based Models: Statistical Challenges and Opportunities. Statistic Views, Wiley.
- Zhuang, L. and Cressie, N. (2014) Bayesian Hierarchical Statistical SIRS Models. Statistical Methods and Applications, 23, 601 – 646.
2013
- Holan, S.H. and Wikle, C.K. (2013) Semiparametric Dynamic Design of Monitoring Networks for Non-Gaussian Spatio-Temporal Data. Spatio-temporal Design: Advances in Efficient Data Acquisition, Jorge Mateu and Werner Muller (Eds.), 269 - 284, Wiley, Chichester, UK.
- Sengupta, A., and Cressie, N. (2013) Hierarchical Statistical Modeling of Big Spatial Datasets Using the Exponential Family of Distributions. Spatial Statistics. 4, 14 - 44.
- Wu, G., Holan, S.H., and Wikle, C.K. (2013) Hierarchical Bayesian Spatio-Temporal Conway-Maxwell Poisson Models with Dynamic Dispersion. Journal of Agricultural, Biological, and Environmental Statistics. 18, 335 – 356.
- Yang, W.H., Wikle, C.K., Holan, S.H., and Wildhaber, M.L. (2013) Ecological Prediction with Nonlinear Multivariate Time-Frequency Functional Data Models. Journal of Agricultural, Biological, and Environmental Statistics. 18, 450 – 474.
2012
- Holan, S.H., Yang, W.H., Matteson, D.S., and Wikle, C.K. (2012) An Approach for Identifying and Predicting Economic Recessions in Real-Time Using Time-Frequency Functional Models. (With Discussion) Applied Stochastic Models in Business and Industry. 28, 485 – 499.
- Wang, J. and Holan, S.H. (2012) Bayesian Multi-Regime Smooth Transition Regression with Ordered Categorical Variables. Computational Statistics and Data Analysis. 56, 4165 – 4179.