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項思佳

哲學博士（Ph.D），教授，碩士生導師，浙江省青年人才

郵箱：sjxiang@zufe.edu.cn

? 最終學歷：

2012.06 – 2014.05, 美國堪薩斯州立大學, 統計學博士, (4.0/4.0) 　　　

2010.08 – 2012.05, 美國堪薩斯州立大學, 統計學碩士, (4.0/4.0) 　

? 研究方向：

混合模型（mixture model）

非參數、半參數估計（nonparametric/semiparametric estimation）

穩健估計（robust estimation）

數據降維（dimension reduction）

? 主持的項目：

國家社科基金，基于高維混合模型的聚類分析的統計推斷，主持，20萬

國家自然科學基金，半參數混合模型及變量選擇研究，主持，20萬

浙江省自然科學基金，混合模型的半參數擴展及其變量選擇的研究，主持，5萬

浙江省統計研究課題 ，混合模型的新估計方法及其應用的研究，主持，1萬

半參數估計在混合模型中的應用，留學回國人員科研啟動基金，主持，3萬元

浙江省教育廳科研項目，混合模型的半參數擴展及其應用的研究，主持，1萬

? 發表的文章：

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.