孫六全，廣州大學經濟與統計學院教授，北京大學理學博士，中國科學院套用數學研究所博士後；現任中國現場統計研究會副理事長，中國機率統計學會副理事長，中國統計教育學會高等教育分會副會長，北京套用統計學會副會長，中國現場統計研究會資源與環境統計分會常務副理事長，中國統計教育學會常務理事，全國工業統計學教學研究會常務理事、監事會副會長、競賽委員會副主任委員，北京大數據協會常務理事。《Statistics and Its Interface》，《Statistics in Biosciences》，《Journal of Biometrics & Biostatistics》，《Journal of Systems Science and Complexity》, 《數理統計與管理》，《套用機率統計》等雜誌Associate Editor，中國第二屆數學名詞審定委員會委員，《中國大百科全書》第三版統計學卷副主編、數學卷編委。在國內外核心刊物發表學術論文120多篇，先後主持或參加了973重大項目，國家自然科學基金重大項目、重點項目和面上項目等18項。
基本介紹
- 中文名：孫六全
- 學位/學歷：博士
- 專業方向：生存分析、生物與醫學統計、復發事件和縱向數據的統計推斷
- 職稱：教授
研究方向,教學方向,科研獎勵,科研項目,出版專著,發表論文,
研究方向
1. 生存分析
2. 生物與醫學統計
3. 復發事件和縱向數據的統計推斷
4. 區間刪失數據的統計分析
5. 各種不完全觀察數據的統計分析
6. 數理統計及其套用
教學方向
1.數理統計
2. 生存分析
科研獎勵
1.2008年獲中科院數學院“突出科研成果獎”。
2.2007年部分工作入選為中科院數學院2007年度十大科研進展。
3.2000年獲北京大學優秀博士學位論文二等獎。
科研項目
1.國家自然科學基金項目：帶信息觀察時間和終止事件的縱向數據聯合建模分析(2018.1-2021.12，負責人)。
2.國家自然科學基金重大項目：大數據的統計學基礎與分析方法(2017.1-2021.12，主要參加者)。
3.國家自然科學基金重點項目：複雜縱向數據的統計推斷(2013.1-2017.12，負責人)。
4.國家自然科學基金項目：帶終止時間的復發事件數據的統計分析及其套用(2012.1-2015.12，負責人)。
5.國家自然科學基金委創新研究群體延續項目：隨機複雜數據與隨機複雜結構的理論方法及其套用（2011.1-2013.12, 參加者）。
6.國家自然科學基金項目: 面板計數數據的統計推斷以及其套用(2010.1-2012.12, 主要參加者)。
7.國家重點基礎研究發展計畫(973計畫)子課題：金融創新產品的設計和定價(2007.1-2011.12，主要參加者)。
8.國家自然科學基金委創新研究群體項目：隨機複雜數據與隨機複雜結構的理論方法及其套用（2008.1-2010.12,參加者）。
9.國家自然科學基金重點項目：複雜刪失數據的統計分析及其套用(2008.1-2011.12，主要參加者)。
10.國家自然科學基金項目：復發事件和成組數據的統計推斷及其套用(2006.1-2008.12，負責人)。
11.留學回國人員基金項目：雙重區間刪失數據的統計分析(2005.9-2006.9，獨立承擔)。
12.國家自然科學基金項目：複雜刪失數據的統計建模及其在生物和醫學中的套用(2005.1-2007.12，主要參加者)。
13.國家自然科學基金: 任意區間刪失數據的統計分析(2001.1-2003.12，負責人)。
14.國家自然科學基金: 不完全數據統計理論及其套用(1999.1-2001.12,主要參加者)。
15.科學院重點創新基金：金融風險防範與對策分析(1998.1-2001.12，主要參加者)。
16.高校博士點專項基金: 工業和醫學中的套用統計(1998.1-2000.12，主要參加者)。
17. 二炮合作項目：武器部件變化的數值建模與預測(1998.9-1999.9，主要參加者)。
18. 高校博士點專項基金：套用統計方法研究(1995.1-1997.12，主要參加者)。
出版專著
1. 孫六全,《10000個科學難題》（數學卷）中"複雜數據的變數選擇問題"和"相依結構下複雜刪失數據統計建模問題"（編著），科學出版社, 2009年。
2. 孫六全，《數學大辭典》數理統計篇中"生存分析"（編著），科學出版社, 2010年。
3. 孫六全，《現代統計研究基礎》中"複雜事件數據的統計分析"（編著），科學出版社，2010年。
發表論文
1997年以來發表的論文如下：
1.Qu, L., Song, X. and Sun, L. (2018). Identification of local sparsity and variable selection for varying coefficient additive hazards models. Comput. Statist. Data Anal. Online. [SCI]
2.Han, M., Sun, L., Liu, Y. and Zhu, J. (2018). Joint analysis of recurrent event data with additive–multiplicative hazards model for the terminal event time. Metrika.Online. [SCI]
3.Chen, X., Ding, J. and Sun, L. (2018). A semiparametric additive rate model for a modulated renewal process. Lifetime Data Anal. Accepted [SCI]
4.Wang, X., Xue, X. and Sun, L. (2018). Regression analysis of restricted mean survival time based on pseudo-observations for competing risks data. Comm. Statist. Theory Methods. Accepted [SCI]
5.Wang, X., Xue, X., Zhou, J. and Sun, L. (2018). An efficient risk estimator with external information under additive hazards model. Acta Math. Appl. Sin. Engl. Ser. Accepted. [SCI]
6.Han, M., Han, D. and Sun L. (2018). A class of partially linear transformation models for recurrent gap times. Comm. Statist. Theory Methods. Accepted. [SCI]
7.He, H., Pan, D., Song X. and Sun L. (2018). Additive mean residual life model with latent variables under right censoring. Statist. Sinica. Online.[SCI]
8.Wang, Z., Ding, J., Sun, L. and Wu, Y. (2018). Tobit quantile regression of left-censored longitudinal data with informative observation times. Statist. Sinica, 28(1).[SCI]
9.Sun, Z., Xue, Y. and Sun, L. (2018). Consistent test for parametric models with right-censored data using projections. Comput. Statist. Data Anal., 118, 112-125. [SCI]
10. Sun, Z., Sun, L., Lu, X., Zhu, J. and Li, Y. (2017). Frequentist model averaging estimation for the censored partial linear quantile regression model. J. Statist. Plann. Inference,189, 1-15. [SCI]
11. Zhang, H., Wang, D. and Sun L.(2017). Regularized estimation in GINAR(p) process. Journal of the Korean Statistical Society, 46, 502-517. [SCI]
12. He, H., Pan, D., Sun, L., Li, Y., Robison, L. and Song, X. (2017). Analysis of a fixed center effect additive rates model for recurrent event data. Comput. Statist. Data Anal.,112, 186-197. [SCI]
13. Cai, J., He, H., Song, X. and Sun, L. (2017). An additive-multiplicative mean residual life model for right censored data. Biometrical Journal. 59(3), 579-592. [SCI]
14. Qu, L., Sun, L. and Liu, L. (2017). Joint modeling of recurrent and terminal events using additive models. Statistics and Its Interface, 10(4), 699-710 [SCI]
15. Zhou, J., Zhu, J. and Sun, L. (2017). A class of Box-Cox transformation models for recurrent event data with a terminal event. Acta Mathematica Sinica, Engl. Ser., 33(8), 1048-1060. [SCI]
16. Zhang, H., Sun, L., Zhou, Y. and Huang, J. (2017). Oracle inequalities and selection consistency for weighted lasso in additive hazards model. Statist. Sinica, 27(4), 1903-1920. [SCI]
17. He, H., Cai, J., Song, X. and Sun, L. (2017). Analysis of proportional mean residual life model with latent variables. Stat. Med.,36(5), 813-826. [SCI]
18. Zhou, J., Zhang, H., Sun, L. and Sun, J. (2017). Joint analysis of panel count data with informative observation process and a dependent terminal event. Lifetime Data Anal., 23(4), 560-584. [SCI]
19. Han, D., Sun, L., Sun, Y. and Qi, L. (2017). Mark-specific additive hazards regression with continuous marks.Lifetime Data Anal., 23(3), 467-494 [SCI]
20. Ding, J. and Sun, L. (2017). Additive mixed effect model for recurrent gap time data. Lifetime Data Anal., 23(2), 223-253. [SCI]
21. Fang, S., Zhang, H., Sun, L. and Wang, D. (2017). Analysis of panel count data with time-dependent covariates and informative observation process. Acta Math. Appl. Sin. Engl. Ser. 33(1), 147-156. [SCI]
22. Han, M., Song, X., Sun, L. and Liu, L. (2016). An additive-multiplicative mean model for marker data contingent on recurrent event with an informative terminal event. Statist. Sinica, 26(3), 1197-1218. [SCI]
23. Du, T., Ding, J. and Sun, L. (2016).Joint modeling and estimation for longitudinal data with informative observation and terminal event times. Comm. Statist. Theory Methods, 45(22), 6521-6539. [SCI]
24. Miao, R., Sun, L. and Tian, G.-L. (2016). Transformed linear quantile regression with censored survival data. Statistics and Its Interface, 9(2), 131–139. [SCI]
25. Fang, S, Zhang, H, Sun, LQ (2016). Joint analysis of longitudinal data with additive mixed effect model for informative observation times. J. Statist. Plann. Inference,169, 43-55. [SCI]
26. Miao, R. Chen, X. and Sun, L. (2016). Analyzing longitudinal data with informative observation and terminal event times. Acta Math. Appl. Sin. Engl. Ser., 32(4), 1035-1052. [SCI]
27. Pei, Y., Du, T. and Sun, L. (2016). Time-varying latent model for longitudinal data with informative observation and terminal event times. SCIENCE CHINA Mathematics, 59(11).[SCI]
28. He, S., Du, T. and Sun, L. (2016). Joint modeling of longitudinal data with a dependent terminal event. Comm. Statist. Theory Methods. 45(3), 813-835. [SCI]
29. Pan, D, He, H, Song, X and Sun, LQ (2015). Regression analysis of additive hazards model with latent variables.J. Amer. Statist. Assoc., 110(511), 1148-1159.[SCI]
30. Ye, P, Sun, LQ, Zhao, X and Wei, X (2015). A semiparametric additive rates model for multivariate recurrent events with missing event categories. Comput. Statist. Data Anal., 89(1), 39-50. [SCI]
31. Dong, L and Sun, LQ (2015). A flexible semiparametric transformation model for recurrent event data. Lifetime Data Anal. 21(1), 20-41. [SCI]
32. Kang, F, Sun, LQ and Zhao, X (2015). A class of transformed hazards models for recurrent gap times. Comput. Statist. Data Anal., 83, 151-167. [SCI]
33. Ye, P, Sun, LQ, Zhao, X and Wei, X (2015). An additive-multiplicative rates model for multivariate recurrent events with event categories missing at random. SCIENCE CHINA Mathematics, 58(6), 1163–1178. [SCI]
34. Sun, Z., Ye, X. and Sun, LQ(2015). Consistent test of error-in-variables partially linear model with auxiliary variables. J. Multivariate Anal., 141(1), 118-131. [SCI]
35. Han, M and Sun, LQ (2014). Joint modeling of longitudinal data with informative observation times and dropouts. Statist. Sinica. 24(4), 1487-1504. [SCI]
36. Hao, M, Song, X and Sun, LQ (2014). Reweighting estimators for additive hazards model with missing covariates. Canad. J. Statist., 42(2), 285-307. [SCI]
37. Dong, C, Zhou, J and Sun, LQ (2014). A class of weighted estimators for additive hazards model in case-cohort studies. Acta Math. Appl. Sin. Engl. Ser. 30(4), 1153-1168. [SCI]
38. Xu, Z; Sun, LQ and Ji, H (2014). Additive mean residual life model with covariate measurement errors. J. Statist. Plann. Inference,153(10), 87–99. [SCI]
39.Zhou, J, Zhao, X and Sun, LQ (2013). A new inference approach for joint models of longitudinal data with informative observation and censoring times.Statist. Sinica, 23(2), 571-593. [SCI]
40.Zhao, H, Zhou, J andSun, LQ (2013). A marginal additive rates model for recurrent event data with a terminal event. Comm. Statist. Theory Methods, 42(14), 2567-2583. [SCI]
41.Sun, Y, Sun, LQ and Zhou, J (2013). Profile local linear estimation of generalized semiparametric regression model for longitudinal data.Lifetime Data Anal.,19(3), 317-349. [SCI]
42.Liu, Y, Sun, LQ and Zhou, Y (2013). Additive transformation models for recurrent events. Comm. Statist. Theory Methods., 42(22), 4043-4055. [SCI]
43.He, S, Wang, F and Sun, LQ (2013). A semiparametric additive rates model for clustered recurrent event data. Acta Math. Appl. Sin. Engl. Ser., 29(1), 55-62. [SCI]
44.Sun, LQ and Kang, F (2013). An additive-multiplicative rates model for recurrent event data with informative terminal event. Lifetime Data Anal., 19(1), 117-137. [SCI]
45.Sun, LQ, Song, X and Zhang, Z (2012). Mean residual life models with time- dependent coefficient under right censoring. Biometrika, 99 (1), 185-197. [SCI]
46.Sun, LQ, Song, X，Zhou, J and Liu, L (2012). Joint analysis of longitudinal data with informative observation times and a dependent terminal event. JASA, 107(498), 688-700. [SCI]
47.Chen, K, Sun, LQ and Tong, X (2012). Analysis of cohort survival data with transformation model. Statist. Sinica, 22 (2), 489-508.[SCI]
48.Song, X, Mu, X and Sun, LQ (2012). Regression analysis of longitudinal data with time-dependent covariates and informative observation times.Scand. J. Statist. 39(2), 248-258. [SCI]
49.Sun, LQ, Song, X. and Mu, X (2012). Regression analysis for the additive hazards model with covariate errors. Comm. Statist. Theory Methods, 41(11), 1911-1932. [SCI]
50.Xie, T, Sun, Z and Sun, LQ (2012). A consistent model specification test for a partial linear model with covariates missing at random.J. Nonparametric Statist.24(4), 841-856. [SCI]
51.Wang, Q, Tong, X and Sun, LQ (2012). Exploring the varying covariate effects in proportional odds models with censored data. J. Multivariate Anal.,109(1), 168-189. [SCI]
52.Wang, C, Sun, J, Sun, LQ, Zhou, J. and Wang, D (2012). Nonparametric estimation of current status data with dependent censoring. Lifetime Data Anal., 18(4), 434-445. [SCI]
53.Zhao, X, Tong, X and Sun, LQ (2012). Joint analysis of longitudinal data with dependent observation times. Statist. Sinica, 22(1), 317-336. [SCI]
54.Zhao, X, Zhou, J and Sun, LQ (2011). Semiparametric transformation models with time-varying coefficients for recurrent and terminal events. Biometrics,67(2), 404-414. [SCI]
55.Sun, LQ, Zhou, X and Guo, S (2011). Marginal regression models with time-varying coefficients for recurrent event data. Stat. Med., 30 (18), 2265-2277. [SCI]
56.Sun, LQ, Song, X and Zhou, J (2011). Regression analysis of longitudinal data with time-dependent covariates in the presence of informative observation and censoring times. J. Statist. Plann. Inference, 141(8), 2902-2919. [SCI]
57.Sun, LQ, Tong, X and Zhou, X (2011). A class of Box-Cox transformation models for recurrent event data. Lifetime Data Anal., 17(2), 280-301. [SCI]
58.Liu, H, Miao, R and Sun, LQ (2011). Analysis of panel data with informative observation and censoring times under biased sampling (Chinese). Sci. China Ser. A., 41(4), 365-376.
59.Sun, LQ, Mu, X, Sun, Z and Tong, X (2011). Semiparametric analysis of longitudinal data with informative observation times. Acta Math. Appl. Sin. Engl. Ser., 27(1), 29-42.[SCI]
60.Sun, LQ, Zhao, X and Zhou, J (2011). A class of mixed models for recurrent event data. Canad. J. Statist., 39(4), 578-590. [SCI]
61.Li, N, Sun, LQ and Sun, J (2010). Semiparametric transformation models for panel count data with dependent observation process. Statistics in Biosciences, 2(2), 191-210. [SCI]
62.Chen, K, Guo, S, Sun, LQ and Wang, J-L (2010). Global partial likelihood for nonparametric proportional hazards models. J. Amer. Statist. Assoc., 105(490), 750-760. [SCI]
63.Song, X, Sun, LQ, Mu, X and Dinse, G E (2010). Additive hazards regression with censoring indicators missing at random. Canad. J. Statist., 38(3), 333-351.[SCI]
64.Sun, LQ, Zhao, Q (2010). A class of mean residual life regression models with censored survival data. J. Statist. Plann. Inference, 140 (11), 3425-3441. [SCI]
65.Zhang, Z, Zhao, X and Sun, LQ (2010). Goodness-of-fit tests for additive mean residual life model under right censoring. Lifetime Data Anal., 16(3), 385-408.[SCI]
66.Liu, L, Mu, X and Sun LQ (2010). A class of additive-accelerated means regression models for recurrent event data. Sci. China Ser. A., 53(12), 3139-3152.[SCI]
67.Sun, LQ and Zhang, Z (2009). A class of transformed mean residual life models with censored survival data. J. Amer. Statist. Assoc., 104 (486), 803-815. [SCI]
68.Sun, LQ, Zhu, L and Sun, J (2009). Regression analysis of multivariate recurrent event data with time-varying covariate effects. J. Multivariate Anal., 100(10), 2214-2223. [SCI]
69.Tong, X, He, X, Sun, LQ and Sun, J (2009). Variable selection for panel count data via nonconcave penalized estimating function. Scand. J. Statist.,36(4), 620-635. [SCI]
70.Dai, J, Sun, LQ and Yang, Z (2009). A general additive-multiplicative rates models for recurrent event data. Sci. China Ser. A, 52(10), 2257-2265. [SCI]
71.Sun, LQ and Tong, X (2009). Analyzing longitudinal data with informative observation times under biased sampling. Statist Probab. Lett., 79(9), 1162-1168.[SCI]
72.Sun, LQ, Guo, S and Chen, M (2009). Marginal regression model with time-varying coefficients for panel data. Comm. Statist. Theory Methods, 38(8), 1241-1261. [SCI]
73.Sun, LQ and Su, B (2008). A class of accelerated means regression models for recurrent event data. Lifetime Data Anal., 14(3), 357-375. [SCI]
74.Sun, LQ and Zhou, X (2008). Inference in the additive risk model with time-varying covariates subject to measurement errors. Statist. Probab. Lett., 78(16), 2559-2566. [SCI]
75.Luo, X, Jiang, F, Sun, LQ and Yang, Z (2008). Marginal regression of multiple type recurrent event data based on transformation models. Gongcheng Shuxue Xuebao,25(2), 26–332. [EI]
76.Liu, H, He, S and Sun, LQ (2008). A general class of semiparametric rates models for recurrent event data. (Chinese) Acta Math. Appl. Sinica,31(4), 671-681.
77.Sun, J, Sun, LQ and Liu, D (2007). Regression analysis of longitudinal data in the presence of informative observation and censoring times. J. Amer. Statist. Assoc. 102(480), 1397-1406.[SCI]
78.Zhang, Z, Sun, LQ, Sun, J and Finkelstein, DM (2007). Regression analysis of failure time data with informative interval censoring. Stat. Med., 26(12), 2533-2546.[SCI]
79.Sun, J, Sun, LQ and Zhu, C (2007). Testing the proportional odds model for interval-censored data. Lifetime Data Anal., 13(1), 37-50. [SCI]
80.Sun, LQ, Wang, L and Sun, J (2006). Estimation of the association for bivariate interval-censored data. Scand. J. Statist., 33(4), 637-649. [SCI]
81.Wang, L, Sun, LQ and Sun, J (2006). A goodness-of-fit test for the marginal Cox model for correlated interval-censored failure time data. Biom. J., 48(6), 1020-1028.[SCI]
82.Sun, LQ, Liu, J, Zhang, M and Sun, J (2006). Modeling the subdistribution of a competing risk. Statist. Sinica, 16(4), 1367-1385. [SCI]
83.Sun, LQ, Zhang, Z and Sun, J (2006). Additive hazards regression of failure time data with covariate measurement errors. Statist. Neerlandica, 60(4), 497-509. [SCI]
84.Sun, LQ, Park, D and Sun, J (2006). The additive hazards model for recurrent gap times. Statist. Sinica, 16(3), 919-932. [SCI]
85.Sun, LQ (2006). The strong law under a semiparametric model for truncated and censored data. Statist. Probab. Lett., 76(14), 1550-1558. [SCI]
86.Gu, MG, Sun, LQ and Zuo, G (2005). A baseline-free procedure for transformation models under interval censorship. Lifetime Data Anal., 11(4), 473-488.[SCI]
87.Sun, J, Park, DH，Sun, LQ and Zhao, X (2005). Semiparametric regression analysis of longitudinal data with informative observation times. J. Amer. Statist. Assoc., 100(471), 882-889. [SCI]
88.Sun, J and Sun, LQ (2005). Semiparametric linear transformation models for current status data.Canad. J. Statist., 33(1), 85-96. [SCI]
89.Zhang, Z, Sun, LQ, Zhao, X and Sun, J (2005). Regression analysis of interval-censored failure time data with linear transformation models. Canad. J. Statist., 33(1), 61-70. [SCI]
90.Zhang, Z, Sun, J and Sun, LQ (2005). Statistical analysis of current status data with informative observation times. Stat. Med., 24(9), 1399-1407. [SCI]
91.Zhou, Y and Sun, LQ (2005). Sequential confidence bands for quantile densities under truncated and censored data. Acta Math. Appl. Sin. Engl. Ser., 21(2), 311-322.
92.Liu, H, Sun, LQ and Zhu, LQ (2005). Asymptotics on semiparametric analysis of multivariate failure time data under the additive hazards model. Acta Math. Appl. Sin. Engl. Ser.,21(2), 237-246.
93.Liu, H and Sun, LQ (2005). A regression method for truncated and censored data. Acta Math. Appl. Sin. ChineseSer., 28(1), 1-10.
94.Gu, MG, Sun, LQ and Huang, C (2004). A universal procedure for parametric frailty models. J. Stat. Comput. Simul., 74(1), 1-13. [SCI]
95.Sun, J, Sun, LQ and Flournoy, N (2004). Additive hazards model for competing risks analysis of the case-cohort design. Comm. Statist. Theory Methods, 33(2), 351-366. [SCI]
96.Sun, LQ, Kim, Y and Sun, J (2004). Regression analysis of doubly censored failure time data using the additive hazards model. Biometrics, 60(3), 637-643. [SCI]
97.Zhou, X, Sun, J and Sun, LQ (2004). A uniform semiparametric approach for longitudinal data analysis. Far EastJ. Theor. Stat., 13(2), 233-256.
98.Sun, LQ (2003). Fixed design nonparametric regression with truncated and censored data. Acta Math. Appl. Sin. Engl. Ser., 19(2), 229-238.
99.Zhou, X and Sun, LQ (2003). Additive hazards regression with missing censoring information. Statist. Sinica, 13(4), 1237-1257. [SCI]
100.Sun, LQ and Wu, G (2002). Edgeworth expansion for the survival function estimator in the Koziol-Green model. Sci. China Ser. A, 45(4), 681-693. [SCI]
101.Maller, A, Sun, LQ and Zhou, X (2002). Estimating the expected total number of events in a process. J. Amer. Statist. Assoc., 97(458), 577-589. [SCI]
102.Sun, LQ and Zhou, X (2002). Regression analysis for a semiparametric model with panel data. Statist. Probab. Lett.,58(3), 309-317.[SCI]
103.Sun, LQ and Zhou, X (2001). Survival function and density estimation for truncated dependent data. Statist. Probab. Lett.,52(1), 47-57. [SCI]
104.Sun, LQ and Ren, H (2001). Bivariate estimation with left-truncated data. Acta Math. Appl. Sin. Engl. Ser., 17(2), 145-156.
105.Sun, LQ (2001). The rate of uniform convergence of the survival function estimator for truncated and censored data. J. Syst. Sci. Complex., 14(1), 93-105.
106.Sun, LQ, Wu, G and Wei, X (2001). Local asymptotic properties of hazard rate estimators for truncated and censored data. J. Syst. Sci. Complex., 14(4), 413-424.
107.Sun, LQ (2000). Edgeworth expansion of the studentized product-limit estimator for truncated and censored data. Sci. China Ser. A, 43(5), 495-508. [SCI]
108.Zhou, X, Sun, LQ and Ren, H (2000). Quantile estimation for left truncated and right censored data. Statist. Sinica, 10(4), 1217-1229. [SCI]
109.Sun, LQ and Zhu, L (2000). A semiparametric model for truncated and censored data. Statist. Probab. Lett., 48(3), 217-227. [SCI]
110.Zhou, Z, Zhou, Y, Sun, LQ and Liu, M (1999). The relative effectiveness analyses of fiscal policies in China. Forecasting, 18(4), 5-8.
111.Fang, B, Zhou, Y and Sun, LQ (1999). The forecast regional analysis of the private motor vehicle market in China. J. Sys. Sci. Sys. Eng., 18(4), 503-513.
112.Sun, LQ and Zhu, L (1999). A Berry-Esseen type bound for kernel density estimators under random censorship. Acta Math. Sin. Chinese Ser., 42(4), 627-636.
113.Sun, LQ and Zheng, Z (1999). Bahadur representation of the kernel quantile estimator under truncated and censored data.Acta Math. Appl. Sin. Engl. Ser., 15(3), 257-268.
114.Sun, LQ and Zheng, Z (1999). The Asymptotics of the integrated square error for the kernel hazard rate estimators with left truncated and right censored data.Systems Sci. Math. Sci.Engl. Ser., 12(3), 251-262.
115.Sun, LQ and Zheng, Z (1999). Asymptotic properties of the estimators of a general class of Von-Mises type functionals under truncated and censored data. Systems Sci. Math. Sci. Chinese Ser., 19(1), 95-105.
116.Sun, LQ and Zheng, Z (1999). Strong representations of the survival function estimator on increasing sets for truncated and censored data. Acta Math. Sci. Engl. Ser., 19(3), 251-260. [SCI]
117.Liu, H and Sun, LQ (1999). Asymptotics of the distance between smoothed PL and quantile processes. J. Math., 19(2), 218-222.
118.Sun, LQ and Zhou, Y (1999). Strong limit theorems for oscillation moduli of PL-process and cumulative hazard process under truncation and censorship with applications. Acta Math. Sin. Engl. Ser., 15(2), 235-244. [SCI]
119.Zhou, Y, Sun, LQ and Yip, P (1999). The almost sure behavior of the oscillation modulus for PL-process and cumulative hazard process under random censorship. Sci. China Ser. A, 42(3), 225-237. [SCI]
120.Sun, LQ and Zheng, Z (1998). A bound on L_1 distances of kernel density estimators for truncated and censored data. Chinese J. Appl. Probab. Statist., 14(3), 266-271.
121.Sun, LQ and Zhou, Y (1998). Strong limit theorems for oscillation moduli of PL-process under left truncation and right censorship. Acta Math. Sin. Chinese Ser., 41(5), 1113-1120.
122.Sun, LQ and Zhou, Y (1998). Asymptotic properties of some hazard rate function estimators under censored data. Acta Math. Appl. Sin. Chinese Ser.,21(4), 597-608.
123.Sun, LQ and Liu, B (1998). The asymptotic distribution of a smoothed Bahadur-Kiefer process under random right censorship. Acta Math. Sci. Chinese Ser., 18(1), 97-108.
124.Sun, LQ and Zhou, Y (1998). Sequential confidence bands for densities under truncated and censored data. Statist. Probab. Lett.,40(1), 31-41. [SCI]
125.Sun, LQ (1997). Bandwidth choice for hazard rate estimators from left truncated and right censored data. Statist. Probab. Lett., 36(2), 101-114. [SCI]
