| Full-scale approximations of spatio-temporal covariance models for large datasets B Zhang, H Sang, JZ Huang Statistica Sinica, 99-114, 2015 | 43 | 2015 |
| Smoothed full-scale approximation of Gaussian process models for computation of large spatial data sets B Zhang, H Sang, JZ Huang Statistica Sinica 29 (4), 1711-1737, 2019 | 18 | 2019 |
| Full scale multi-output Gaussian process emulator with nonseparable auto-covariance functions B Zhang, BA Konomi, H Sang, G Karagiannis, G Lin Journal of computational physics 300, 623-642, 2015 | 18 | 2015 |
| Bayesian inference of spatio-temporal changes of Arctic sea ice B Zhang, N Cressie | 17 | 2020 |
| Inference for errors-in-variables models in the presence of systematic errors with an application to a satellite remote sensing campaign B Zhang, N Cressie, D Wunch Technometrics 61 (2), 187-201, 2019 | 8 | 2019 |
| Estimating spatial changes over time of Arctic sea ice using hidden 2× 2 tables B Zhang, N Cressie Journal of Time Series Analysis 40 (3), 288-311, 2019 | 6 | 2019 |
| Bayesian clustering of spatial functional data with application to a human mobility study during COVID-19 B Zhang, H Sang, ZT Luo, H Huang The Annals of Applied Statistics 17 (1), 583-605, 2023 | 5 | 2023 |
| Statistical properties of atmospheric greenhouse gas measurements: Looking down from space and looking up from the ground B Zhang, N Cressie, D Wunch Chemometrics and Intelligent Laboratory Systems 162, 214-222, 2017 | 5 | 2017 |
| Frequent marine heatwaves hidden below the surface of the global ocean D Sun, F Li, Z Jing, S Hu, B Zhang Nature Geoscience 16 (12), 1099-1104, 2023 | 3 | 2023 |
| Inferring Changes in Arctic Sea Ice through a Spatio-Temporal Logistic Autoregression Fitted to Remote-Sensing Data B Zhang, F Li, H Sang, N Cressie Remote Sensing 14 (23), 5995, 2022 | 2 | 2022 |
| Efficient and effective calibration of numerical model outputs using hierarchical dynamic models Y Chen, X Chang, B Zhang, H Huang The Annals of Applied Statistics 18 (2), 1064-1089, 2024 | | 2024 |
| Spatial linear regression with covariate measurement errors: Inference and scalable computation in a functional modeling approach J Cao, S He, B Zhang Journal of Computational and Graphical Statistics, 2023 | | 2023 |
| SUPP: Inference for Errors-in-Variables Models in the Presence of Systematic Errors with an Application to a Satellite Remote Sensing Campaign B Zhang, N Cressie, D Wunch Technometrics 61 (2), 2019 | | 2019 |
| Wiley StatsRef: Environmental Informatics N Cressie, S Burden, C Shumack, A Zammit-Mangion, B Zhang | | 2016 |
| Environmental informatics N Cressie, S Burden, C Shumack, A Zammit-Mangion, B Zhang | | 2016 |
| Statistical Methods for Large Spatial and Spatio-temporal Datasets B Zhang | | 2015 |
| S1 Details of the MCMC Algorithm B Zhang, H Sang, ZT Luo, H Huang | | |
| Research Online PJ Molino, L Garcia, EM Stewart, M Lamaze, B Zhang | | |
