师资队伍
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姓名:项思佳

项思佳

哲学博士(Ph.D),副教授,硕士生导师

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:

国家自然科学基金,半参数混合模型及变量选择研究,主持,20

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

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

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

Ø 入选人才情况

“浙江省高校中青年学科带头人”,浙江省教育厅,2017.

Ø 发表的文章:

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

[2] 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.

[3] 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.

[4] Xiang, S. and Yao, W. (2018). Semiparametric mixtures of nonparametric regressions. Annals of the Institute of Mathematical Statistics. 70, 131-154.

[5] 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.

[6] 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.

[7] Xiang, S., Yao, W., andSeo, B.(2016). Semiparametric mixture: Continuous scale mixture approach. Computational Statistics & Data Analysis, 103, 413-425.

[8] 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.

[9] 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.

[10] 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.

[11] 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.


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