高维统计、机器学习

1.Huang, M., Wang, S., Yao, W., Chen, Y. (2018). Statistical inference and applications of

mixture of varying coefficient models. Scandinavian Journal of Statistics, 45, 618-643.

2.Zhang, Y., and Wang, S. (2018). Monotone function estimation in partially linear Models.

Statistics and Its Interface, 11, 19-29.

3.Huang, M., Wang, S., Wang, H., and Jin, T. (2018). Maximum smoothed likelihood estimation for a

class of semiparametric Pareto mixture densities. Statistics and Its Interface, 11, 31-40.

4.Huang, G., Wang, S., Wang, X., You, N. (2016). An empirical Bayes method for genotyping and SNP

detection using multi-sample next-generation sequencing data. Bioinformatics, 32, 32403-245.

5.Wang, S., Huang, M., and Wu, X., and Yao, W. (2016). Mixture of functional linear models and

its application to CO2-GDP functional data. Computational Statistics and Data Analysis, 97, 1

15.

6.Wen, C, Wang, X., and Wang, S. (2015). Laplace error penalty based variable selection in high

dimension. Scandinavian Journal of Statistics, 42, 685-700.

7.Wang, S., Yao, W., and Huang, M. (2014). A note on the identifiability of nonparametric and

semiparametric mixtures of GLMs. Statistics and Probability Letters, 93, 41-45.

8.Huang, M., Li, R., and Wang, S. (2013). Nonparametric mixture of regression models. Journal of

the American Statistical Association, 108, 929-941.