MyselfI am an Associate Professor of statistics at Texas A&M University.
For my CV, click here (last updated August 27, 2014).
Research interest Spatial (and Temporal) Statistics Environmental Statistics Covariance models for processes on a sphere Numerical Model Evaluation Compuational Methods for Large Data Sets Likelihood Methods Data Assimilation Statistics in Climate application Selected publications Jun, M., Katzfuss, M., Hu, J., Johnson, V. (2014). Assessing fit in Bayesian models for spatial processes. Environmetrics, In press Jun, M. (2014). Matern-based nonstationary cross-covariance models for global processes. Journal of Multivariate Analysis, Vol 128, pp. 134-146. Roh, S., Genton, M.G., Jun, M., Szunyogh, I., Hoteit, I. (2013). Observation Quality Control with a Robust Ensemble Kalman Filter. Monthly Weather Review, Vol 141, pp. 4414-4428.
Jun, M., Park, E.S. (2013). Multivariate receptor models for spatially correlated multi-pollutant data. Technometrics, 55, pp. 309-320.
Jun, M., Genton, M.G. (2012). A test for stationarity of spatio-temporal random fields on planar and spherical domains. Statistica Sinica., 22, pp. 1737-1764.
Vaughan, A., Jun, M., Park, C. (2012). Statistical inference and visualization in scape-space for spatially dependent images. Journal of the Korean Statistical Society, 41, pp. 115-135. PDF
Jun, M. (2011). Nonstationary cross-covariance models for multivariate processes on a globe. Scandinavian Journal of Statistics, Vol 38, pp. 726-747. PDF Data page
Sang, H., Jun, M., Huang, J.Z. (2011). Covariance approximation for large multivariate spatial datasets with an application to multiple climate model errors. Annals of Applied Statistics, Vol. 5, No. 4, pp. 2519-2548, PDF
Jun, M., Szunyogh, I., Genton, M.G., Zhang, F., Bishop, C.H. (2011). A statistical investigation of the sensitivity of ensemble based Kalman filters to covariance filtering. Monthly Weather Review, 139, pp. 3036-3051. PDF
Jun, M., Stein, M.L. (2008). Nonstationary covariance models for global data. Annals of Applied Statistics, 2, pp. 1271-1289. PDF
Jun, M., Knutti, R., Nychka, D.W. (2008). Spatial Analysis to Quantify Numerical Model Bias and Dependence: How Many Climate Models Are There? Journal of the American Statistical Association, 103, pp. 934-947. PDF
Jun, M., Knutti, R., Nychka, D.W. (2008). Local eigenvalue analysis of CMIP3 climate model errors. Tellus, 60A, pp. 992-1000. PDF
Jun, M., Stein, M.L. (2007). An approach to producing space-time covariance functions on spheres. Technometrics, Volume 49, No. 4, Oct 2007, pp. 468-479. PDF
Jun, M., Stein, M.L. (2004). Statistical Comparison of Observed and CMAQ Modeled Daily Sulfate Levels. Atmospheric Environment, Volume 38, Issue 27, pp. 4427-4436. PDF Supplementary material Grants NSF DMS-1208421, PI, Jul 2012 - Jun 2015. NSF DMS-0906532, PI, Aug 2009-Jul 2012. NSF ATM-0620624, co-PI, Sep 2006-Aug 2010. Work-related Links STATMOS (May 2014 - ) IAMCS supported by KAUST EnKF 2014 PASI 2014
Editor (Book review) JABES (Journal of Agricultural, Biological, and Environmental Statistics): click for guildeline Associate Editor STAT Associate Editor JKSS (Journal of the Korean Statistical Society)
TeachingSTAT 211: course webpage e-learning
JSM 2010 Statistical Climatology conference 2012 ENKF 2014