![]()
-
副教授
- 电子邮箱：0cfde6a93bebfbf93a81f2836b5cbc62564ca52797af4e34099290e0e3e130a5d3eb11f5a9cbc81dcbe6c5dc03b92898ed32bd59b2a1a20f55c4e3da2756dd12a15fe36c60375866888a72951ce50a49f96a477d9705c6ed72c9c6e4726eb9caf5e02692726e729b9cf3ca04306ff6bfa034d10bceaf388d66adf9626c068b53
- 联系方式：+86-551-63600560
- 学位：博士
访问量：
-
[21]A relative error-based estimation with an increasing number of parameters, Communications in Statistics- Theory and Methods, 2018, 47: 196-209.
-
[22]A robust estimation for the extended t-process regression model, Statistics and Probability Letters, 2020, 157.
-
[23]Minimum -divergence estimator and hierarchical testing in loglinear models under product-multinomial sampling, Journal of Statistical Planning and Inference, 2009, 139: 3488-3500.
-
[24]Marker selection via maximizing the partial area under the ROC curve of linear risk scores, Biostatistics, 2011, 12(2): 369-385.
-
[25]Group variable selection and estimation in the tobit censored response model, Computational Statistics and Data Analysis, 2013, 60: 80-89.
-
[26]Random weighting approximation for Tobit regression models withlongitudinal data, Computational Statistics and Data Analysis, 2014, 79: 235-247.
-
[27]Group Variable Selection for Relative Error Regression, Journal of Statistical Planning and Inference, 2016, 175: 40-50.
-
[28]Least product relative error estimation, Journal of Multivariate Analysis, 2016, 144: 91-98.
-
[29]Extended t-process regression models, Journal of Statistical Planning and Inference, 2017, 189: 38-60.
-
[30]Tobit quantile regression of left-censored longitudinal data with informative observation times, Statistica Sinica, 2018, 28: 527-548.
