| Hierarchical nearest-neighbor Gaussian process models for large geostatistical datasets A Datta, S Banerjee, AO Finley, AE Gelfand Journal of the American Statistical Association 111 (514), 800-812, 2016 | 300 | 2016 |
| A case study competition among methods for analyzing large spatial data MJ Heaton, A Datta, AO Finley, R Furrer, J Guinness, R Guhaniyogi, ... Journal of Agricultural, Biological and Environmental Statistics 24 (3), 398-425, 2019 | 133 | 2019 |
| Mapping local and global variability in plant trait distributions EE *Butler, A *Datta, H Flores-Moreno, M Chen, KR Wythers, F Fazayeli, ... Proceedings of the National Academy of Sciences, 201708984, 2017 | 87 | 2017 |
| Non-separable Dynamic Nearest-Neighbor Gaussian Process Models for Large spatio-temporal Data With an Application to Particulate Matter Analysis A Datta, S Banerjee, AO Finley, NAS Hamm, M Schaap Annals of Applied Statistics 10 (3), 1286-1316, 2016 | 69 | 2016 |
| CoCoLasso for High-dimensional Error-in-variables Regression A Datta, H Zou Annals of Statistics 45 (6), 2400-2426, 2017 | 60 | 2017 |
| Methods for analyzing large spatial data: A review and comparison MJ Heaton, A Datta, A Finley, R Furrer, R Guhaniyogi, F Gerber, ... arXiv preprint arXiv:1710.05013 22, 2017 | 49 | 2017 |
| Efficient algorithms for Bayesian nearest neighbor Gaussian processes AO Finley, A Datta, BD Cook, DC Morton, HE Andersen, S Banerjee Journal of Computational and Graphical Statistics 28 (2), 401-414, 2019 | 45 | 2019 |
| On nearest‐neighbor Gaussian process models for massive spatial data A Datta, S Banerjee, AO Finley, AE Gelfand Wiley Interdisciplinary Reviews: Computational Statistics 8 (5), 162-171, 2016 | 30 | 2016 |
| Spatial disease mapping using directed acyclic graph auto-regressive (DAGAR) models A Datta, S Banerjee, JS Hodges, L Gao Bayesian Analysis, 2019 | 17 | 2019 |
| Applying nearest neighbor gaussian processes to massive spatial data sets: Forest canopy height prediction across tanana valley alaska AO Finley, A Datta, BC Cook, DC Morton, HE Andersen, S Banerjee arXiv preprint arXiv:1702.00434, 2017 | 16 | 2017 |
| Practical Bayesian modeling and inference for massive spatial data sets on modest computing environments† L Zhang, A Datta, S Banerjee Statistical Analysis and Data Mining: The ASA Data Science Journal 12 (3 …, 2019 | 13 | 2019 |
| Spatial factor models for high-dimensional and large spatial data: an application in forest variable mapping D Taylor-Rodriguez, AO Finley, A Datta, C Babcock, HE Andersen, ... Statistica Sinica 29, 1155, 2019 | 12 | 2019 |
| Regularized Bayesian transfer learning for population level etiological distributions A Datta, J Fiksel, A Amouzou, S Zeger Biostatistics, 1-22, 2020 | 8* | 2020 |
| Bayesian estimation of MSM population size in Côte d’Ivoire A Datta, W Lin, A Rao, D Diouf, A Kouame, JK Edwards, L Bao, TA Louis, ... Statistics and Public Policy 6 (1), 1-13, 2019 | 7 | 2019 |
| Estimating sizes of key populations at the national level: considerations for study design and analysis JK Edwards, S Hileman, Y Donastorg, S Zadrozny, S Baral, ... Epidemiology (Cambridge, Mass.) 29 (6), 795, 2018 | 7 | 2018 |
| spNNGP: Spatial Regression Models for Large Datasets using Nearest Neighbor Gaussian Processes AO Finley, A Datta, S Banerjee https://cran.r-project.org/web/packages/spNNGP/index.html, 2017 | 7 | 2017 |
| Robustness of trait connections across environmental gradients and growth forms H Flores‐Moreno, F Fazayeli, A Banerjee, A Datta, J Kattge, EE Butler, ... Global Ecology and Biogeography 28 (12), 1806-1826, 2019 | 5 | 2019 |
| BRISC: bootstrap for rapid inference on spatial covariances A Saha, A Datta Stat 7 (1), e184, 2018 | 5 | 2018 |
| A note on cross-validation for lasso under measurement errors A Datta, H Zou Technometrics 62 (4), 549-556, 2020 | 4 | 2020 |
| Generalized Bayesian quantification learning J Fiksel, A Datta, A Amouzou, S Zeger arXiv preprint arXiv:2001.05360, 2020 | 3 | 2020 |
Andrew FinleyDepartment of Forestry, Michigan State UniversityEmail verificata su msu.edu
