- L. Zhang, A. Datta, and S. Banerjee, “Practical Bayesian Inference for Massive Spatial Data on Modest Computing Environments,” Statistical Analysis and Data Mining, To appear.
- A. O. Finley, A. Datta, B. C. Cook, D. C. Morton, H. E. Andersen, and S. Banerjee, “Efficient algorithms for Bayesian Nearest Neighbor Gaussian Processes,” Journal of Computation and Graphical Statistics, Accepted.
- D. Taylor-Rodriguez et al., “Spatial Factor Models for High-Dimensional and Large Spatial Data: An Application in Forest Variable Mapping,” Statistica Sinica, Accepted.
- A. Datta et al., “Bayesian Estimation of MSM Population Size in Côte d’Ivoire,” Statistics and Public Policy, vol. 6, no. 1, pp. 1–13, 2019.
- A. Datta, H. Zou, and S. Banerjee, “Bayesian high-dimensional regression for change point analysis,” Statistics and Its Interface, vol. 12, no. 2, pp. 253–264, 2019.
- J. K. Edwards et al., “Estimating sizes of key populations at the national level: considerations for study design and analysis,” Epidemiology, vol. 29, no. 6, pp. 795–803, 2018.
- M. J. Heaton et al., “A Case Study Competition Among Methods for Analyzing Large Spatial Data,” Journal of Agricultural, Biological and Environmental Statistics, Dec. 2018.
- A. Saha and A. Datta, “BRISC: bootstrap for rapid inference on spatial covariances,” Stat, p. e184, 2018.
- A. Datta and H. Zou, “CoCoLasso for high-dimensional error-in-variables regression,” Annals of Statistics, vol. 45, no. 6, pp. 2400–2426, 2017.
- E. E. Butler et al., “Mapping local and global variability in plant trait distributions,” Proceedings of the National Academy of Sciences, vol. 114, no. 51, pp. E10937–E10946, 2017.
- A. Datta, S. Banerjee, A. O. Finley, and A. E. Gelfand, “On nearest-neighbor Gaussian process models for massive spatial data,” Wiley Interdisciplinary Reviews: Computational Statistics, vol. 8, no. 5, pp. 162–171, 2016.
- A. Datta, S. Banerjee, A. O. Finley, N. A. S. Hamm, and M. Schaap, “Nonseparable dynamic nearest neighbor Gaussian process models for large spatio-temporal data with an application to particulate matter analysis,” Annals of Applied Statistics, vol. 10, no. 3, pp. 1286–1316, 2016.
- A. Datta, S. Banerjee, A. O. Finley, and A. E. Gelfand, “Hierarchical Nearest-Neighbor Gaussian Process Models for Large Geostatistical Datasets,” Journal of the American Statistical Association, vol. 111, no. 514, pp. 800–812, 2016.
- A. Datta, S. Banerjee, and J. S. Hodges, “Spatial disease mapping using Directed Acyclic Graph Auto-Regressive (DAGAR) models,” Under review.
- A. Datta, J. Fiksel, A. Amouzou, and S. Zeger, “Regularized Bayesian transfer learning for population level etiological
distributions,” Under review.
- H. Flores-Moreno et al., “Robustness of trait connections between multiple plant organs across environmental gradients and growth forms,” Under review.
- A. Datta and H. Zou, “A note on cross-validation for Lasso under measurement errors,” Under review.
- A. Datta, A. Pita, A. Rao, B. Sithole, Z. Mnisi, and S. Baral, “Size Estimation of Key Populations in the HIV Epidemic in eSwatini using incomplete and misaligned capture-recapture data,” Under review.