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 | 247 | 2008 |
Nonstationary covariance models for global data M Jun, ML Stein | 180 | 2008 |
An approach to producing space–time covariance functions on spheres M Jun, ML Stein Technometrics 49 (4), 468-479, 2007 | 145 | 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 | 107 | 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 | 86 | 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 | 85 | 2011 |
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 | 66 | 2008 |
Statistical comparison of observed and CMAQ modeled daily sulfate levels M Jun, ML Stein Atmospheric Environment 38 (27), 4427-4436, 2004 | 63 | 2004 |
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 | 62 | 2019 |
Non‐stationary cross‐covariance models for multivariate processes on a globe M Jun Scandinavian Journal of Statistics 38 (4), 726-747, 2011 | 59 | 2011 |
Spherical process models for global spatial statistics J Jeong, M Jun, MG Genton Statistical science: a review journal of the Institute of Mathematical …, 2017 | 57 | 2017 |
A class of Matérn-like covariance functions for smooth processes on a sphere J Jeong, M Jun Spatial Statistics 11, 1-18, 2015 | 50 | 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 | 43 | 2014 |
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 | 41 | 2015 |
A test for stationarity of spatio-temporal random fields on planar and spherical domains M Jun, MG Genton Statistica Sinica, 1737-1764, 2012 | 38 | 2012 |
Matérn-based nonstationary cross-covariance models for global processes M Jun Journal of Multivariate Analysis 128, 134-146, 2014 | 37 | 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 | 31 | 2020 |
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 | 25 | 2019 |
Covariance models on the surface of a sphere: when does it matter? J Jeong, M Jun Stat 4 (1), 167-182, 2015 | 20 | 2015 |