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刘天庆

发表于: 2017-11-30   点击: 


基本情况




















































































































































姓名: 刘天庆





















































































































































性别:




















































































































































职称: 副教授




















































































































































所在系别: 概率统计系




















































































































































最高学历: 研究生




















































































































































最高学位: 理学博士




















































































































































Email:




















































































































































备注: http://www.researchgate.net/profile/Tianqing_Liu



































































































































































































































































































































































































































































详细情况
所在学科专业: 概率统计
所研究方向: 复杂数据, 高维数据和大数据的统计理论研究
教育经历:

2000.9-2004.7东北师范大学数学与统计学院数学与应用数学专业 大学本科

2004.9-2010.6东北师范大学数学与统计学院概率论与数理统计专业 硕博连读

2011.10-2013.4 美国George Washington 大学统计系 博士后

2010.10-2014.9 吉林大学数学所 博士后
工作经历:

2010.7-2014.9 吉林大学数学学院 讲师

2014.9-至今 吉林大学数学学院 副教授
科研项目:

1. 缺失数据下的基于经验似然的稳健推断函数,国家自然科学青年基金(No.11201174), 执行时间:2013.01-2015.12,资助金额 23万.

2. 基于秩的稳健经验似然, 教育部新教师基金(No. 20110061120004), 执行时间:2012.01-2014.12,资助金额 4万.

3. 缺失数据下转换回归模型的稳健经验似然推断,  吉林省青年科研基金(No.20150520054JH) , 执行时间:2015.01-2017.12,资助金额 6万.

学术论文:

1. Liu, T., Lin, N. and *Zhang, B. (2009), Empirical likelihood for balanced ranked-set sampled data, Science China Mathematics, 52, 1351-1364. (SCI)

2. Liu, T., Lin, N., Shi, N. and *Zhang, B. (2009), Information criterion-based clustering with order-restricted candidate profiles in short time-course microarray experiments, BMC Bioinformatics, 10: 146. (SCI)

3. Zhang, B., Liu, T. and *Bai, Z. (2010), Analysis of rounded data from dependent sequences, Annals of the Institute of Statistical Mathematics, 62, 1143-1173. (SCI)

4. Liu, T. Zhang, B., Hu, G. and *Bai, Z. (2010), Revisit of Sheppard corrections in linear regression, Science China Mathematics, 53, 1435-1451. (SCI)

5. Yuan, X., *Liu, T., Lin, N. and *Zhang, B. (2010), Combining conditional and unconditional moment restrictions with missing responses, Journal of Multivariate Analysis, 101, 2420-2433. (SCI)

6. Li , W., Liu, T. and *Bai, Z. (2012), Rounded data analysis based on ranked set sample, Statistical Papers, 53,439–455 (SCI)

7. *Liu, T. and Yuan, X. (2012), Combining quasi and empirical likelihoods in generalized linear models with missing responses, Journal of Multivariate Analysis, 111, 39-58. (SCI)

8. *Liu, T.,Yuan, X., Lin, N. and *Zhang, B. (2012),Rank-based empirical likelihood inference on medians of k populations, Journal of Statistical Planning and Inference,142, 1009-1026.(SCI)

9. Liu, T.,Yuan, X., Li, Z. and *Li, Y. (2013), Empirical and weighted conditional likelihoods for matched case-control studies with missing covariates, Journal of Multivariate Analysis, 119, 185-199. (SCI)

10. *Liu, T. and Yuan, X. (2013), Random rounded integer-valued autoregressive conditional heteroskedastic process, Statistical Papers, 54:645–683. (SCI)

11. *Liu, T., Bai, Z. and *Zhang, B. (2014), Weighted estimating equation: modified GEE in longitudinal data analysis , Frontiers of Mathematics in China, 9: 329-353. (SCI)

12. *Li ,Y., Yolken, R., Cowan, D. N.,   Boivin, M. R., Liu T. and  Niebuhr, D. W. (2015), Biomarker identification and effect estimation on schizophrenia – a high dimensional data analysis, Frontiers in Public Health, 3: 75. (SCI)

13. Liu, T. and *Yuan, X., (2016), Weighted quantile regression with missing covariates using empirical likelihood, Statistics: A Journal of Theoretical and Applied Statistics, 50:89-113. (SCI)

14. Zhang, Z., *Liu, T.  and * Zhang, B., (2016), Jackknife empirical likelihood inferences for the population mean with ranked set samples,  Statistics and Probability Letters, 108: 16-22 (SCI)

15. Yuan, X., Lin, N., Dong, X. and *Liu, T. , (2017),  Weighted quantile regression for longitudinal data using empirical likelihood,  Science China Mathematics, 60: 147–164. (SCI)

16. Liu, T., *Wu, C. O., Li, Z. and Li, Y. (2018) , Semiparametric random-effects conditional density models for longitudinal analysis with concomitant intervention,  Statistica Sinica , 28 : 1333-1349. (SCI)

17. Liu, T. and *Yuan, X., (2020) Doubly robust augmented-estimating-equations estimation with nonignorable nonresponse data, Statistical Papers, 61:2241–2270. (SCI)

18. Yuan, X., Wang, Y. and *Liu, T. (2020) Variable selection for semiparametric random-effects conditional density models with longitudinal data, Communications in Statistics-Theory and Methods, 49: 977-996. (SCI)

19. Liu, T. and *Yuan, X., (2020) Adaptive empirical likelihood estimation with nonignorable

nonresponse data, Statistics, 54: 1-22. (SCI)

20.*Liu, T. and Yuan, X., (2020)  Empirical likelihood-based weighted rank regression with missing covariates, Statistical Papers,  61: 697–725.  (SCI)

21. Liu, T., *Yuan, X. and Sun, J. (2021) Weighted rank estimation for nonparametric transformation models with doubly truncated data, Journal of the Korean Statistical Society 50:1–24. (SCI)

22. Yuan, X, Li, H. and *Liu, T. (2021) Empirical likelihood inference for rank regression with doubly truncated data, AStA Advances in Statistical Analysis 105:25–73. (SCI)

23. Liu, T., *Yuan, X. and *Sun, J. (2021)  Weighted rank estimation for nonparametric transformation models with nonignorable missing data. Computational Statistics and Data Analysis 153: 107061.

社会兼职: 美国《Mathematical Reviews》评论员



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