项思佳

哲学博士（Ph.D），教授，硕士生导师，浙江省青年人才

邮箱：sjxiang@zufe.edu.cn

Ø 最终学历：

2012.06 – 2014.05, 美国堪萨斯州立大学, 统计学博士, (4.0/4.0) 　　　

2010.08 – 2012.05, 美国堪萨斯州立大学, 统计学硕士, (4.0/4.0) 　

Ø 研究方向：

混合模型（mixture model）

非参数、半参数估计（nonparametric/semiparametric estimation）

稳健估计（robust estimation）

数据降维（dimension reduction）

Ø 主持的项目：

国家社科基金，基于高维混合模型的聚类分析的统计推断，主持，20万

国家自然科学基金，半参数混合模型及变量选择研究，主持，20万

浙江省自然科学基金，混合模型的半参数扩展及其变量选择的研究，主持，5万

浙江省统计研究课题 ，混合模型的新估计方法及其应用的研究，主持，1万

半参数估计在混合模型中的应用，留学回国人员科研启动基金，主持，3万元

浙江省教育厅科研项目，混合模型的半参数扩展及其应用的研究，主持，1万

Ø 发表的文章：

1. Xiang, S., Yao, W. (2020). Semiparametric mixtures of regressions with single-index for model based clustering. Advances in Data Analysis and Classification, 14, 261-292.

2. Xiang, S., Yao, W., and Yang, G. (2019). An Overview of Semiparametric Extensions of Finite Mixture Models. Statistical Science, 34(3), 391-404.

3. Xu, L., Xiang, S., and Yao, W. (2019). Robust maximum Lq-likelihood estimation of joint mean-covariance models for longitudinal data. Journal of Multivariate Analysis, 171, 397-411.

4. Yang, G., Yao, W., and Xiang, S. (2019). Sure independence screening in ultrahigh dimensional generalized additive models. Journal of Statistical Planning and Inference， 199， 126-135.

5. Xiang, S. And Yao, W. (2018). Semiparametric Mixtures of Nonparametric Regressions. Annals of the institute of statistical mathematics, 70, 131-154.

6. Wu, J., Yao, W., and Xiang, S. (2017). Computation of an efficient and robust estimator in a semiparametric mixture model, Journal of Statistical Computation and Simulation, 87, 2128-2137.

7. Yang, L., Xiang, S. and Yao, W. (2017). Robust fitting of mixtures of factor analyzers using the trimmed likelihood estimator. Communications in Statistics - Simulation and Computation, 42(2), 1280-1291.

8. Xiang, S., Yao, W. and Seo, B. (2016). Semiparametric mixture: Continuous scale mixture approach. Computational Statistics & Data Analysis, 103, 413-425.

9. Xiang, S. and Yao, W. (2016). A new information criterion based bandwidth selection method for nonparametric regressions. Journal of Statistical Computation and Simulation, 86(17), 3446-3455.

10. Li, M., Xiang, S. and Yao, W. (2016). Robust estimation of the number of components for mixtures of linear regression models. Computational Statistics, 31(4), 1539-1555.

11. Xiang, S., Yao, W. and Wu, J. (2014). Minimum profile Hellinger distance estimation for a semiparametric mixture model. The Canadian Journal of Statistics, 42(2), 246-267.

12. Cernicchiaro, N., Renter, D.G., Xiang, S., White, B.J. and Bello, N.M. (2013). Hierarchical Bayesian modeling of heterogeneous variances in average daily weight gain of commercial feedlot cattle. The Journal of Animal Science, 91, 2910-2919.

13. Xiang, S., Yao, W. and Wu, J. (2014). Minimum profile Hellinger distance estimationfor a semiparametric mixture model. The Canadian Journal of Statistics, 42(2), 246-267.

14. Cernicchiaro, N., Renter, D.G., Xiang, S., White, B.J. and Bello, N.M. (2013).Hierarchical Bayesian modeling of heterogeneous variances in average daily weightgain of commercial feedlot cattle. The Journal of Animal Science, 91, 2910-2919.