Abhirup Datta
Abhirup Datta
Assistant Professor, Biostatistics, Bloomberg School of Public Health, Johns Hopkins University
Email verificata su jhu.edu - Home page
Citata da
Citata da
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
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
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
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
CoCoLasso for High-dimensional Error-in-variables Regression
A Datta, H Zou
Annals of Statistics 45 (6), 2400-2426, 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
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
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
Spatial disease mapping using directed acyclic graph auto-regressive (DAGAR) models
A Datta, S Banerjee, JS Hodges, L Gao
Bayesian Analysis, 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
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
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
Regularized Bayesian transfer learning for population level etiological distributions
A Datta, J Fiksel, A Amouzou, S Zeger
Biostatistics, 1-22, 2020
Bayesian estimation of MSM population size in Cte 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
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
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
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
BRISC: bootstrap for rapid inference on spatial covariances
A Saha, A Datta
Stat 7 (1), e184, 2018
A note on cross-validation for lasso under measurement errors
A Datta, H Zou
Technometrics 62 (4), 549-556, 2020
Generalized Bayesian quantification learning
J Fiksel, A Datta, A Amouzou, S Zeger
arXiv preprint arXiv:2001.05360, 2020
Il sistema al momento non pu eseguire l'operazione. Riprova pi tardi.
Articoli 1–20