Assistant Professor of Statistics, University of South Carolina, August 2010 — Current
Ph.D., Statistical Science, Duke University, 2010
M.S., Statistical Science, Duke University, 2008
B.S., Mathematical Statistics, Nankai University, 2006
High-dimensional statistical inference and computation, machine learning, Bayesian econometrics
Minhua Chen, Hao Wang, Xuejun Liao and Lawrence Carin, Bayesian Learning of Sparse Gaussian Graphical Models. [pdf]
H. Wang, Coordinate Descent Algorithm for Covariance Graphical Lasso. Statistics and Computing (Forthcoming) [html]
Y. He, X. Chen, and H. Wang, Modeling correlated sample via sparse matrix Gaussian graphical models. Journal of Zhejiang University Science C: Computer and Electronics (Forthcoming) [html]
H. Wang and N. S. Pillai, 2013, On a Class of Shrinkage Priors for Covariance Matrix Estimation. Journal of Computational and Graphical Statistics (Forthcoming) [html]
H. Wang, The Bayesian Graphical Lasso and Efficient Posterior Computation. Bayesian Analysis 7(2):771— 790, 2012. [html]
H. Wang and S. Z. Li, Efficient Gaussian Graphical Model Determination under G-Wishart Prior Distributions. Electronic Journal of Statistics 6 (2012):168— 198 [html]
H. Wang and J. P. Reiter, Multiple Imputation for Sharing Precise Geographies in Public Use Data. Annals of Applied Statistics 6 (2012): 229— 252 [html]
H. Wang, C. Reeson and C. M. Carvalho, Dynamic Financial Index Models: Modeling Conditional Dependencies via Graphs. Bayesian Analysis 6 (2011): 639— 664[html]
H. Wang and C. M. Carvalho, Simulation of Hyper-Inverse Wishart Distributions for Non-decomposable Graphs. Electronic Journal of Statistics 4 (2010):1467— 1470 [html]
H. Wang, Sparse Seemingly Unrelated Regression Modelling: Applications in Econometrics and Finance. Computational Statistics and Data Analysis 54 (2010): 2866— 2877[html]
H. Wang and M. West, Bayesian analysis of matrix normal graphical models. Biometrika 96 (2009):821— 834 [html]
Stat 720 Time Series Analysis (Spring 2013).
Stat 509 Statistics for Engineers (Fall 2012).
Stat 513 Theory of Statistical Inference (Fall 2012).
Stat 110 Introduction to Statistical Reasoning (Spring 2012).
Stat 509 Statistics for Engineers (Fall 2011).
Stat 720 Time Series Analysis (Spring 2011).
Stat 509 Statistics for Engineers (Fall 2010).