Heng  Peng
 

         

 

 Assistant Professor

 Department of Mathematics

 

 

 Education

  
    B.S.  (1997), The University of Science and Technology of China  (USTC)
    M.S.  (2000), The University of Science and Technology of China
    Ph.D. (2003), The Chinese University of Hong Kong  (CUHK)

 

 

 Working Experience

 
   12/2003-6/2006    Research Associate,  Department of Operation Research and Financial
      Engineering, Princeton University
   9/2006-Present    Assistant Professor, Department of Mathematics, HKBU
   

 

  Teaching

 
  STAT 3710  Multivariate Analysis  and Data Mining
  STAT 3820  Life Insurance and Life Contingencies
  STAT 3830  Time Series  and Forecasting
  SCI 7520   Actuarial Statistics

 

 

 Research Interesting

 

   Financial Econometric

      Bioinformatics

      Data-analytic Modeling

      Model Selection

      Nonparametric Methods

 

 

 Publications and Manuscripts

 

  Lin, H.Z., Zhou, L., Peng, H. and Zhou, X. H., (2011), The selection and combination of biomarkers using ROC method for disease classification and prediction, The Canadian Journal of Statistics, 39, 324-343.

Li, G. R., Feng, S. Y. and Peng, H. (2011), A Profile-type Smoothed Score Function for a Varying Coefficient Partially Linear Model,  Journal of Multivariate Analysis, 102, 372-385.

Peng, H. and Huang, T. (2011), Penalized Least Squares for Single Index Models, Journal of Statistical Planning and Inference, 141, 1362-1379.

Li, G. R., Peng, H. and Zhu, L. X., (2011), Nonconcave Penalized M-estimation with Diverging Number of Parameters,  Statistica Sinica, 21, 391-420.

Peng,H. and Cui, X. (2010), Estimation and inference for partial linear model with multivariate function component, In Preparation.

 Zhang, C. Q., Peng, H. and Zhang, J. T. (2010), Two Samples Tests for Functional Data, Communications in Statistics - Theory and Methods, No. 39, 559-578. 

Zhang, W.Y. and Peng H.,  (2010), Simultaneous confidence band and hypothesis test in generalized varying-coefficient models, Journal of Multivariate Analysis , 101, No. 7, 1656-1680.

  Lam, Y. C., Cheng, C. W., Peng, H., Law, C. K., Huang, X. Z. and Bian, Z. X. (2009),  Cancer patients' attitudes towards Chinese medicine: a Hong Kong survey, Chinese Medicine, 4:25.
 

Ait-Sahalia, Y., Fan, J. and Peng, H. (2009).  Nonparametric transition-based tests for diffusions, Journal of American Statistical Association, Vol 104, No 487, 1102-1116.

  Hui, J., Miao, B.Q., Ning, J. and Peng, H., (2008), Nonparametric Estimation for Contamination Distribution, Applied Mathematics-a Journal of Chinese Universities Series B., Vol 23, Issue 2, 175-182.

Zhu, L.X., Miao, B.Q., and Peng, H.(2006), On Sliced Inverse Regression with large dimensional covariates, Journal of American Statistical Association, Vol 101, No. 474, 630-643.  

Fan, J., Peng H., and Huang, T., (2005),  Semilinear high-dimensional model for normalization of mircoarray data: a theoretical analysis and partial consistency (with discussion) , Journal of American Statistical Association, Vol 100, No. 471, 781-813.

Fan, J. and Peng H., (2004), Nonconcave penalized likelihood with a diverging number of parameters, The annals of statistics, Vol 32, No 3, 928-961.   

Liu, D.H., Miao, B.Q. and Peng, H., (2002), Convergence for Kernel Estimation of Error Density in M-Estimator (in Chinese), Chinese Journal of Applied Probability and Statistics, Vol 18, No.2, 125-133.

Peng, H.and Miao, B.Q., (2001), Inferences on Negative Dependent Change Point of Components of Random Vector (in Chinese), Journal of China university of Science and Technology, Vol 31, No.1, 21-29.

Miao, B.Q., Dai, X.L., Wei, L.S., Peng H. and Wang, X.F., (2000), Statistical analysis for the curricular teaching assessment questionnaire (in Chinese), High Education Assessment of China, Vol 19, No. 2.

 

 Update Oct. 12, 2010

 

  

 

 

 

 

 

 

 

 

FSC1205, Fong Shu Chuen Building  Department of Mathematics, The Hong Kong Baptist University, Kowloon Tong, Hong Kong 
 
    

      hpeng@math.hkbu.edu.hk

        (852)-3411 7021