| Spatial analysis to quantify numerical model bias and dependence: how many climate models are there? M Jun, R Knutti, DW Nychka Journal of the American Statistical Association 103 (483), 934-947, 2008 | 252 | 2008 |
| Nonstationary covariance models for global data M Jun, ML Stein | 181 | 2008 |
| An approach to producing space–time covariance functions on spheres M Jun, ML Stein Technometrics 49 (4), 468-479, 2007 | 146 | 2007 |
| Generic Escherichia coli contamination of spinach at the preharvest stage: effects of farm management and environmental factors S Park, S Navratil, A Gregory, A Bauer, I Srinath, M Jun, B Szonyi, ... Applied and environmental microbiology 79 (14), 4347-4358, 2013 | 113 | 2013 |
| Spatio-temporal asymmetry of local wind fields and its impact on short-term wind forecasting AA Ezzat, M Jun, Y Ding IEEE transactions on sustainable energy 9 (3), 1437-1447, 2018 | 100 | 2018 |
| Covariance approximation for large multivariate spatial data sets with an application to multiple climate model errors H Sang, M Jun, JZ Huang The Annals of Applied Statistics, 2519-2548, 2011 | 92 | 2011 |
| Spatio-temporal short-term wind forecast: A calibrated regime-switching method AA Ezzat, M Jun, Y Ding The annals of applied statistics 13 (3), 1484, 2019 | 72 | 2019 |
| Local eigenvalue analysis of CMIP3 climate model errors M Jun, R Knutti, DW Nychka Tellus A: Dynamic Meteorology and Oceanography 60 (5), 992-1000, 2008 | 65 | 2008 |
| Statistical comparison of observed and CMAQ modeled daily sulfate levels M Jun, ML Stein Atmospheric Environment 38 (27), 4427-4436, 2004 | 65 | 2004 |
| Spherical process models for global spatial statistics J Jeong, M Jun, MG Genton Statistical science: a review journal of the Institute of Mathematical …, 2017 | 62 | 2017 |
| Non‐stationary cross‐covariance models for multivariate processes on a globe M Jun Scandinavian Journal of Statistics 38 (4), 726-747, 2011 | 60 | 2011 |
| A class of Matérn-like covariance functions for smooth processes on a sphere J Jeong, M Jun Spatial Statistics 11, 1-18, 2015 | 52 | 2015 |
| Multifactorial effects of ambient temperature, precipitation, farm management, and environmental factors determine the level of generic Escherichia coli contamination on … S Park, S Navratil, A Gregory, A Bauer, I Srinath, B Szonyi, K Nightingale, ... Applied and Environmental Microbiology 81 (7), 2635-2650, 2015 | 48 | 2015 |
| Farm management, environment, and weather factors jointly affect the probability of spinach contamination by generic Escherichia coli at the preharvest stage S Park, S Navratil, A Gregory, A Bauer, I Srinath, B Szonyi, K Nightingale, ... Applied and Environmental Microbiology 80 (8), 2504-2515, 2014 | 47 | 2014 |
| Temporal and spatial analysis of per and polyfluoroalkyl substances in surface waters of Houston ship channel following a large-scale industrial fire incident NA Aly, YS Luo, Y Liu, G Casillas, TJ McDonald, JM Kaihatu, M Jun, ... Environmental Pollution 265, 115009, 2020 | 41 | 2020 |
| A test for stationarity of spatio-temporal random fields on planar and spherical domains M Jun, MG Genton Statistica Sinica, 1737-1764, 2012 | 39 | 2012 |
| Matérn-based nonstationary cross-covariance models for global processes M Jun Journal of Multivariate Analysis 128, 134-146, 2014 | 38 | 2014 |
| Observation quality control with a robust ensemble Kalman filter S Roh, MG Genton, M Jun, I Szunyogh, I Hoteit Monthly Weather Review 141 (12), 4414-4428, 2013 | 31 | 2013 |
| Baseline data for distribution of contaminants by natural disasters: results from a residential Houston neighborhood during Hurricane Harvey flooding G Bera, K Camargo, JL Sericano, Y Liu, ST Sweet, J Horney, M Jun, ... Heliyon 5 (11), 2019 | 28 | 2019 |
| A spatio-temporal track association algorithm based on marine vessel automatic identification system data I Ahmed, M Jun, Y Ding IEEE Transactions on Intelligent Transportation Systems 23 (11), 20783-20797, 2022 | 21 | 2022 |