, H. Wang.,M. Chen.Principal Component Analysis of Functional Data based on Constant Numerical Characteristics. Revue des Nouvelles Technologies de l'Information, Advances in Theory and Applications of High Dimensional and Symbolic Data Analysis
, R. Guan., J. Wu, L. Shangguan,H. Wang.Multiple linear Regression modeling for compositional data. Neurocomputing
, A. Zheng., H. Wang,L. Huang.The M-estimator for Functional Linear Regression model[J]. Statistics & Probability Letters
, Z. Qin., H. Wang,M. Chen.Principal Component Analysis for Probabilistic Symbolic Data: a More Generic and Accurate Algorithm. Advances in Data Analysis and Classification
, S. Wang, H. Cui, H. Wang,L. Huang.Sieve M-estimator for a Semi-functional Linear model. Science China-Mathematics
,N. Li, X. Shi, M. Chen,H. Wang.Principal Component Analysis for Normal-Distribution-Valued Symbolic Data, IEEE Transactions on Cybernetics
, R.Guan., L.Shangguan,H.Wang.Principal Component Analysis for Compositional Data Vectors. Computational Statistics.
, Long.., W, Guan, R, Feng, H, Zheng, H, Wang, C, Wang,H.Updating Input-Output tables with Benchmark Table Series. Economic Systems Research
,H.Wang（Editors）,J.Henseler,W.W.Chin,V.Esposito Vinzi.Handbook of Partial Least Square：Concepts，Methods and Application. Springer