南京审计大学统计与数据科学学院
林金官 中共党员
1965年1月生，安徽省来安县人，男，博士，统计学教授、博士生导师。目前担任江苏省政府统计与大数据研究院院长、南京审计大学统计科学大数据研究院院长。现主要从事非线性统计、计量经济、金融统计与风险度量、统计诊断、面板数据分析和统计应用等方面的研究工作。2000年以来, 在国内外核心期刊上发表论文一百余篇，其中SCI和SSCI收录论文八十余篇。至目前，已培养博士生15人，培养硕士生数十人，另先后与8位博士后进行合作研究。
办公室：崇真楼301
电 话：86-025-58312983
Emai l ：jglin@nau.edu.cn
通讯地址：南京市浦口区雨山西路86号
邮 编：211815
1. 学术兼职
2013-2017、2018-20222年度教育部统计学类教学指导委员会委员；
全国工业统计学教学研究会副会长；
中国现场统计研究会资源与环境学会副理事长；
中国现场统计研究会工程概率统计学会副理事长；
江苏省概率统计学会秘书长；
江苏省统计学联盟副理事长；
《系统科学与数学》、《数理统计与管理》、《统计与决策》、《统计学报》杂志编委，《数理统计与管理》副主编。
2. 受教育经历
2000/09- 2002/12东南大学经济管理学院，研究生/博士；
1986/09- 1988/07华东师范大学统计系，研究生/硕士；
1982/09 –1986/07华东师范大学数学系，本科/学士。
3. 研究工作经历
2016/07至今南京审计大学统计科学与大数据研究院、amjs澳金沙门线路首页教授、学科带头人；曾任统计与数学学院院长。
2007/09–2007/11、2012/05–2012/06香港浸会大学访问。
2006/07–2016/06东南大教授，统计学博士生导师、学科带头人；曾任东南大学数学系副主任。
1988/07–2006/07江苏教育学院数学系讲师、副教授、教授。曾任江苏教育学院工会副主席、数学系副主任。
2003/03- 2005/02东南大学管理科学与工程博士后流动站博士后， 2005/03- 2007/02东南大学数学博士后流动站博士后。
4. 获奖情况（2000年以来）
[1] 林金官、赵彦勇、汪红霞、黄性芳. 基于Copula相关函数的风险度量及其应用，江苏省统计局，第十五届江苏省统计科研优秀成果奖二等奖，2018年6月；
[2] 赵彦勇、林金官、黄性芳、汪红霞. 自适应模型的保跳估计，江苏省统计局，第十五届江苏省统计科研优秀成果奖三等奖，2018年6月；
[3] 林金官，朱建国，黄超，庄晴韵，近极值事件的广义态密度估计及其在股票数据分析中的应用，江苏省统计局，第十二届江苏省统计科研优秀成果奖二等奖，2012年5月；
[4] 解锋昌，林金官（导师），一类零过度数据的建模及诊断分析，国家统计局， 第十一届全国统计科研优秀成果奖二等奖，2012年12月；
[5] 林金官, 韦博成, 非线性回归模型异方差检验的局部渐近功效, 南京市人民政府，南京市第七届自然科学优秀学术论文奖二等奖, 2007年10月；
[6] 韦博成，林金官等, 复杂数据的统计诊断方法及其应用, 国家统计局第七届全国统计科研优秀成果奖（课题类）一等奖，2004年6月；
[7] 林金官，韦博成（导师）, 回归模型的异方差和变离差检验, 国家统计局第七届全国统计科研优秀成果奖（博士论文类）一等奖，2004年6月；
[8] 林金官，韦博成, 非线性随机效应模型的异方差性检验, 南京市第五届（2001-2002年度）自然科学优秀学术论文奖三等奖，2003年10月。
5. 2000年以来承担的基金情况
[1] 江苏省第七次全国人口普查委托项目“江苏长三角地区人口与经济社会发展研究”，3万，2021.12-2022.2；
[2] 南京市第七次全国人口普查委托项目“南京人口对高质量发展分析研究”，3万，2021.12-2022.2；
[3] 南京市秦淮区第七次全国人口普查委托项目“秦淮区人口对高质量发展分析研究”，2.5万，2021.12-2022.2；
[4] 盐城市统计局委托项目“GDP视角下盐城市经济发展状况的研究”，19万，2021.12-2022.3.
[5] 全国统计科学研究（计划）重点项目“基于金融混频数据的波动率模型分析及其应用”(2020LZ19),5万，2020.9-2022.9.
[6] 主持国家自然科学基金“金融资产收益变动率的统计推断及其应用研究”（11971235），52万（直接经费），2020.1-2023.12；
[7] 主持国家自然科学基金重点项目子项目“多源异构数据的融合、特征提取与分析方法”（11831008），50万，2019.1-2022.12；
[8] 主持南京市统计局重点项目“城市经济密度比较与发展潜力研究”（2018A004），5万，2018.12-2019.5；
[9] 主持江苏省第三次全国农业普查研究课题，3万，2018.5-2018.12；
[10] 主持国家自然科学基金“一类经济计量模型的统计分析及其应用研究”（11571073），50万（直接经费），2016.1-2019.12；
[11] 主持2014年度江苏省重点统计研究课题“大数据环境下政府统计业务流程优化整合研究”，5万，2014.9-2015.9；
[12] 主持全国统计科学研究（计划）重点项目“基于Copulas相关函数的风险度量及其应用”（2014LZ40），2万，2014.11-2016.10；
[13] 主持江苏省自然科学基金项目“具有复杂结构的非正规正交设计的研究与应用”(BK20141326），10万，2014.7-2017.6；
[14] 主持教育部博士点基金（博导类）“基于Copula相关函数的近极值事件的统计推断及其应用”（20120092110021），12万，2013.1-2015.12.
[15] 主要参与国家社会科学基金项目“基于复杂面板数据模型的物价波动研究”（12BTJ015，排名第二），15万，2012.7-2015.12.
[16] 主持国家自然科学基金“具有复杂相关结构的统计模型的理论与应用研究”（11171065）, 45万2012.1-2015.12;
[17] 主持江苏省自然科学基金项目“重尾模型中近极值数据的统计推断及其应用”(BK2011058), 20万，2011.6-2013.12;
[18] 主持国家统计局全国统计科学研究（计划）项目“模糊回归分析及其在经济数据分析中的应用”(2010LC27），2010.11-2011.11；
[19] 主持浙江省统计局重点课题“基于对称分布模型的统计数据分析”，1万，2010.6- 2011.6；
[20] 主持联迪恒星(南京)信息系统有限公司横向课题“数据挖掘应用分析的系统开发”，8万，2010.12-2011.12；
[21] 主持江苏省自然科学基金项目“重尾数据的统计分析及其应用”(BK2008284），9万，2008.9-2010.12；
[22] 主持国家自然科学基金项目“纵向数据的参数建模及其统计诊断”(10671032），26万，2007.1-2009.12；
[23] 主持国家社会科学基金项目“社会经济发展过程中复杂动态随机系统的统计分析”（04BTJ002），7万，2004.7--2008.11；
[24] 主持国家统计局全国统计科学研究（计划）项目(重点项目)“纵向数据模型的协方差结构及其统计诊断” (LXZ0415)，2万，2004.11--2006.11；
[25] 主要参与国家自然科学基金项目“非线性纵向数据分析及其统计诊断”(10371016)，16万，2004.1-2006.12;
[26] 主要参与国家社会科学基金项目“复杂数据的统计诊断及其应用”（02BTJ001，排名第二），7万，2002.7-2003.12.
6. 2010年以来的主要论著(*表示通讯作者)
2022年度
[1] Zhou,X.C., Wang, J.Y., Wang H.X. and Lin,J.G. Panel semiparametric quantile regression neural network for electricity consumption forecasting. Ecological Informatics(SCI期刊), 2022, 67, 101489.
[2] 王江艳，林金官.基于约束B样条光滑方法的协方差函数估计. 中国科学: 数学.2021, doi: 10.1360/SSM-2020-0116
2021年度
[1] Liu,Y., Yang,A.J., Lin,J.G. and Yao,J.L. A new method of valuing American options based on Brownian models. Communications in Statistics-Theory and Methods(SCI期刊), 2021, 50(20), 4809-4821.
[2] 汪红霞，林金官*，黄性芳. 时空模型的局部众数回归. 中国科学: 数学, 2021, 51(4): 615-630.
[3] 汪红霞, 罗学洪, 林金官*, 唐星. 误差分布未知下时空模型的自适应非参数估计. 数学年刊，2021, 42(2): 125-148.
[4] 龙伟芳,叶绪国,林金官. 跳-扩散模型中即时波动率的门限多次幂变差核估计. 数学的实践与认识，51（14）：194-205.
[5] 王江艳,林金官,陈旭岚. 基于长收益率序列信息的时变波动率估计及实证研究. 应用概率统计，37(5):523-543.
2020年度
[1] Han,Z.C., Lin,J.G.* and Zhao,Y.Y. Adaptive semiparametric estimation for single index models with jumps. Computational Statistics and Data Analysis(SCI期刊), 2020, 151, 107013.
[2] Hu,G.K. and Lin,J.G. Performance of Preliminary Test Estimators for Error Variance Based on W, LR and LM Tests. Journal of Systems science and Complex(SCI期刊), 2020, 33:1200-1211.
[3] Kong,X.B., Lin,J.G. and Liu,G.Y. Asymptotics for the systematic and idiosyncratic volatility
with large dimensional high-frequency data. Random Matrices: Theory and Applications(SCI期刊), 2020, 9(3): 2050007.
[4] Yang,A.J.,Tian,Y.Z.,Li,Y.X. and Lin,J.G. Sparse Bayesian variable selection in kernel probit model for analyzing high-dimensional data. Computational Statistics(SCI期刊), 2020, 35:245-258.
[5] Zhao,J.Q., Zhao,Y.Y. Lin,J.G. et.al. Estimation and testing for panel data partially linear single-index models with errors correlated in space and time. Random Matrices: Theory and Applications(SCI期刊), 2020, 9(2): 2150005.
[6] 韩忠成, 林金官, 汪红霞. 基于局部多项式展开的多元非参数模型贝叶斯带宽选择. 数理统计与管理，2020, 39(1)：93-103.
[7] 郝红霞,林金官. 基于线性样条的门限随机波动率模型及其实证研究.数理统计与管理，2020, 39(2)：323-331.
[8] 王杰, 杨爱军,林金官. 基于AST分布和HGARCH模型的金融资产收益率波动非对称性刻画与VaR预测.数理统计与管理，2020, 39(6)：1121-1140.
2019年度
[1] Waled,K., Lin,J.G.*, Han,Z.C., Zhao,Y.Y. and Hao,H.X. Test for Heteroscedasticity in Partially Linear Regression Models. Journal of Systems science and Complex(SCI期刊), 2019,32, 1194-1210.
[2] Zhao,Y.Y. and Lin,J.G.* Estimation and test of jump discontinuities in varyingcoefficient models with empirical applications. Computational Statistics and Data Analysis(SCI期刊), 2019, 139, 145-163.
[3] Zhao,Y.Y., Lin,J.G.*, Huang,X.F. and Wang,H.X. Iterative weighted estimation based on variance modelling in linear regression models. Communications in Statistics - Theory and Methods(SCI期刊), 2019, 48(9), 2599-2614.
[4] 赵彦勇，林金官*，杜秀丽. 带跳单指标模型的半参数跳点检测估计. 中国科学: 数学, 2019, 49(7):1021-1040.
[5] 苍玉权，赵彦勇，林金官. 基于带跳时变系数模型的PPI 与 CPI 相关性研究. 统计研究, 36(2): 101-111.
[6] 郝红霞，林金官，汪红霞. 杠杆效应检验的一种新方法. 应用概率统计，2019， 35(5): 353-468.
[7] Waled, K., Lin.J.G*. and Feng,C.L. Testing the heteroscedasticity in single-index models. Chinese Journal of Applied Probability and Statistics, 2019, 35(4):408-424.
[8] 郝红霞，林金官，汪红霞. GARCH模型的贝叶斯局部影响分析及其应用. 数理统计与管理，2019, 38(4)：602-618.
[9] 刘悦, 杨爱军, 林金官. 基于机制转换模型的碳排放权期权定价. 数理统计与管理，2019, 38(2)：225-234.
2018年度
[1] Ye,X.G., Lin,J.G.*, Zhao,Y.Y..A two-step estimation of diffusion processes using noisy Observations. Journal of Nonparametric Statistics(SCI期刊), 2018.2, 30(1): 145-181.
[2] Hao,H.X, Lin,J.G.*,et al. Estimation and application of semiparametric stochastic volatility models based on kernel density estimation and hidden Markov models. Applied Stochastic Models in Business and Industry(SSCI期刊), 2018, 34:355-375.
[3] 林金官，郝红霞，汪红霞. 基于拟似然方法的股票收益与波动率关系及其应用研究. 统计研究，2018，35(5):99-109.
[4] Zhao, Y. Y.,Lin,J.G.*, et al. Two-stage orthogonality based estimation for semiparametric varying-coefficient models and its applications in analyzing AIDS data. Biometrical Journal(SCI期刊). 2018,60:79-99.
[5] Chen,X.P., LinJ.G., et al. Matrix Image Method for Ranking Nonregular Fractional Factorial Designs. Acta Mathematicae Applicatae Sinica, English Series(SCI期刊). 2018,34(4): 742-751.
[6] Zhao, Y.Y., Lin,J.G.*, et al. Iterative weighted estimation based on variance modelling in linear regression models. Communications in Statistics - Simulation and Computation(SCI期刊), DOI:10.1080/03610918.2018.1458136.
[7] Yang,A.J., Xiang,J., Yang,H. and Lin.J.G. Sparse Bayesian Variable Selection in Probit Model for Forecasting U.S. Recessions Using a Large Set of Predictors(SCI期刊). Computational Economics, 2018, 51:1123-1138.
[8] Cao,C.Z., Wang,Y., Shi,J. and Lin,J.G. Measurement Error Models for Replicated Data Under Asymmetric Heavy-Tailed Distributions. Computational Economics(SCI期刊), 2018, 52:531-553.
[9] Zhou,X.C., Xu,Y,Z. and Lin,J.G. Wavelet estimation in time-varying coefficient time series models with measurement errors. Communications in Statistics - Theory and Methods(SCI期刊), 2018, 47(10): 2504-2519.
[10] Liu,G.X., Du,X.L.,Wang,M.M. and Lin,J.G. Semiparametric jump-preserving estimation for single-index models. Journal of Nonparametric Statistics(SCI期刊), 2018, 30(3): 556-580.
[11] Sun,H.H., Lin,J.G. Testing for Homogeneity of Exponential Correlation Nonlinear Mixed Models Based on M-estimation. Chinese Journal of Applied Probability and Statistics, 2018, 34(2) :156-168.
2017年度
[1] Zhao, Y.Y., Lin,J.G.*, et al. Jump-detection-based estimation in time-varying coefficient models and empirical applications. TEST(SCI期刊), 2017, 26:574-599.
[2] Lin,J.G.*,Zhang,K.S. and Zhao,Y.Y.Nonparametric estimation of multivariate multiparameter conditional copulas. Journal of the Korean Statistical Society(SCI期刊), 2017,46:126-136.
[3] Zhao, Y. Y.,Lin,J.G.*, Wang, H.X. Robust bootstrap estimates in heteroscedastic semi-varying coefficient models and applications in analyzing Australia CPI data. Communications in Statistics-Simulation and Computation(SCI期刊), 2017,46(4): 2638-2653.
[4] Han, Z. C., Lin,J.G.*, et al. A robust and efficient estimationmethod for nonparametric models with jump points. Communications in Statistics-Simulation and Computation(SCI期刊), 2017,46(8): 6283-6297.
[5] Chen,X.P., Lin.J.G.*,et al. Designs containing partially clear main effects. Statistics and Probability Letters(SCI期刊), 2017, 121:12-17.
[6] Du, X.L., Lin,J.G. and Zhou,X.L. Parameter estimation for multivariate diffusion processes with the time inhomogeneously positive semidefinite diffusion matrix. Communications in Statistics - Theory and Methods(SCI期刊), 2017, 46(22): 11010-11025.
[7] Xie,F.C., Lin,J.G. and Wei,B.C. Score test for homogeneity of dispersion in generalized Poisson mixed models with excess zeros. Communications in Statistics-Simulation and Computation(SCI期刊), 2017, 46(1): 301-314.
[8] Yang,A.J., Jiang,X.J.,Shu,L. and Lin,J.G. Bayesian variable selection with sparse and correlation priors for high-dimensional data analysis. Computational Statistics(SCI期刊), 2017, 32:127-143.
[9] Zhou,X.C., Xu,Y.Z. and Lin,J.G.. Wavelet estimation in varying coefficient models for
censored dependent data. Statistics and Probability Letters(SCI期刊), 2017, 122:179-189.
[10] 陈雪平，林金官，汪红霞，黄性芳. 区组大小不等的主效应设计. 中国科学: 数学, 2017, 47(6): 765-778.
[11] Yang,A.J., Jiang,X.J., Xiang,L.M. and Lin.J.G. Sparse Bayesian variable selection in multinomial probit regression model with application to high-dimensional datan classification. Communications in Statistics-Simulation and Computation(SCI期刊), 2017, 46(12): 6137-6150.
2016年度
[1] Chen,X.P. and Lin,J.G..Orthogonal Arrays Robust to A Specified Set of Nonnegligible Effects. Journal of Systems Science and Complex(SCI期刊), 29,pp: 531-541,2016.
[2]. Hao,H.X., Lin,J.G*.,et al.Bayesian case influence analysis for GARCH models based on
Kullback–Leibler divergence.Journal of the Korean Statistical Society(SCI期刊), 45,pp:595-609, 2016.
[3]Wang,H.X., Lin,J.G. and Wang,J.D.. Nonparametric spatial regression with spatial autoregressive error structure. Statistics (SCI期刊), 50,pp:60-75,2016.
[4]. Zhao,Y.Y., Lin,J.G.* and Huang,X.F.. Nonparametric estimation in generalized varying- coefficient models based on iterative weighted quasi-likelihood method. Computational Statistics(SCI期刊), 31,pp:247-268,2016.
[5].Zhang,K.S., Lin,J.G.* and Xu,P.R. A New Class of Copulas involved Geometric Distribution: Estimation and Applications. Insurance: Mathematics and Economics (SCI, SSCI期刊), 66,pp:1-10, 2016.
[6]. Zhao,Y.Y.,Lin,J.G*,et.al. Adaptive jump-preserving estimates in varying-coefficient models.
Journal of Multivariate Analysis(SCI期刊),149,pp:65-80,2016.
2015年度
[1] Lin.J.G.*, Chen,X.P., et,al. Generalized variable resolution designs. Metrika (SCI期刊),78(7),pp:873-884,2015.
[2]Lin.J.G.*, Zhao,Y.Y. and Wang,H.X.. Heteroscedasticity diagnostics in varying-coefficient partially linear regression models and applications in analyzing Boston housing data. Journal of Applied Statistics(SCI期刊), 42(11),pp:2432-2448,2015.
[3] Ye,X.G., Lin,J.G.*, Zhao,Y.Y. and Hao,H.X..Two-step estimation of the volatility functions in diffusion models with empirical applications. Journal of Empirical Finance (SCI, SSCI期刊), 33,pp:135-159,2015.
[4] Chen,X.P., Lin,J.G.* and Wang,H.X.. Construction of main-effect plans orthogonal through the block factor. Statistics and Probability Letters(SCI期刊), 106,pp: 58-64,2015.
[5]. Zhao,Y.Y., Lin,J.G.*, Xu,P.R. and Ye,X.G. Orthogonality-projection-based estimation for semi- varying coefficient models with heteroscedastic errors. Computational Statistics and Data Analysis(SCI期刊), pp:204-221,2015.
[6] Zhou,X.C. andLin,J.G.Asymptotics of a wavelet estimator in the nonparametric regression model with repeated measurements under a NA error process. RACSAM(SCI期刊), pp: 109: 153-168, 2015.
[7]. Zhu, C.H., Gao,Q.B. and Lin,J.G. Uniform tail asymptotics for the aggregate claims with stochastic discount in the renewal risk models. SCIENCE CHINA: Mathematics(SCI期刊), 58(5),pp: 1079-1090,2015.
[8]Chen,X.P., Lin,J.G.*, Wang,X.D. and Huang,X.F.. Further results on orthogonal arrays for the estimation of global sensitivity indices based on alias matrix. Statistical Methods and Applications(SCI期刊), 24,pp:411-426,2015.
[9] Cao,C.Z., Lin,J.G., etal.Multivariate measurement error models for replicated data under heavy-tailed distributions. Journal of Chemometrics(SCI期刊), 29(8),pp:457-466.
[10] Du,X.L., Lin,J.G., Liu,G.X. and Zhou,X.Q..A physical parameter identification method of Lévy-driven vibratory systems based on multipower variation processes. Journal of Sound and Vibration(SCI期刊), 343,pp:216-229,2015.
[11]. Wang,H.X., Lin,J.G. and Wang,J.D..Local Linear Estimation for Spatiotemporal Models
Based on Least Absolute Deviation. Communications in Statistics-Theory and Methods (SCI期刊), 44,pp:1508-1522, 2015.
[12] Sun,H.H. and Lin,J.G.. Diagnostics of Variance of the Error in Mixed Effects Linear Models Based on M-estimation. Communications in Statistics-Theory and Methods (SCI期刊), 44,pp: 1779-1785, 2015.
[13]Chen,X.P., Lin,J.G.* and Huang,X.F.. Construction of main effects plans orthogonal through the block factor based on level permutation. Journal of the Korean Statistical Society(SCI期刊),44,pp: 538-545,, 2015.
2014年度
[1] Cao,C.Z., Lin,J.G. and Shi, J.Q.. Diagnostics on nonlinear model with scale mixtures of skew-normal and first-order autoregressive errors. Statistics(SCI期刊), 48(5),pp: 1033- 1047,2014.
[2]. Huang, C. and Lin, J.G.*. Modified maximum spacings method for generalized extreme value distribution and applications in real data analysis. Metrika (SCI期刊), 77,pp:867- 894,2014.
[3]. Wang,K.Y., Lin,J.G. and Yang,Y.. Asymptotics for Tail Probability of Random Sums with a Heavy-Tailed Number and Dependent Increments. Communications in Statistics-Theory and Methods (SCI期刊), 43,pp: 2595-2604, 2014
[4]. Xie,F.C., Lin,J.G. and Wei, B.C.. Bayesian zero-inflated generalized Poisson regression model: estimation and case influence diagnostics. Journal of Applied Statistics (SCI期刊), 41( 6), 1383-1392, 2014
[5]. Yang,Y., Lin,J.G. and Tan,Z.Q.. The finite-time ruin probability in the presence of Sarmanov dependent financial and insurance risks. Appl. Math. J. Chinese Univ. (SCI期刊), 29(2),pp: 194-204,2014.
[6]. Zhou,X.C. and Lin,J.G.. COMPLETE q-ORDER MOMENT CONVERGENCE OF MOVING AVERAGE PROCESSES UNDER ϕ-MIXING ASSUMPTIONS. APPLICATIONS OF MATHEMATICS (SCI期刊), 1, 69–83,2014.
[7]. Zhou,X.C. and Lin,J.G.. Wavelet Estimator in Nonparametric Regression Model with Dependent Error’s Structure. Communications in Statistics-Theory and Methods (SCI期刊), 43,pp: 4707-4722, 2014.
[8]. Zhou,X.C. and Lin,J.G..Empirical likelihood for varying-coefficient semiparametric mixed- effects errors-in-variables models with longitudinal data. Statistical Methods and Applications(SCI期刊), 23, pp: 51–69,2014.
[9] Zhou,X.C. and Lin,J.G.*.Empirical likelihood inference in mixture of semiparametric varying-coefficient models for longitudinal data with non-ignorable dropout. Statistics(SCI期刊),48(3),pp:668-684, 2014.
2013年度
[1]. Lin, J. G.* and Cao, C, Z.. On estimation of measrement error models with replication under heavy- tailed distributions. Computational Statistics(SCI期刊), 28,pp:809–829, 2013.
[2]. Huang, C., Lin, J. G.*, Ren, Y. Y. Testing for the shape parameter of generalized extreme value distribution based on the Lq-likelihood ratio statistic. Metrika(SCI期刊), 76, pp: 641- 671, 2013.
[3]. Zhang, K. S., Lin, J. G., Huang C.. Some new results on weighted geometric mean for copulas. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems (SCI期刊) ,21(2)，pp:277-288, 2013.
[4]. Zhao. H. X., Lin, J. G.* An approximately optimal non-parametric procedure for analyzing exchangeable binary data with random cluster sizes. Computational Statistic (SCI期刊), 28,pp:2029–2047, 2013.
[5]. Zhou, X. C. & Lin, J. G.*. Semiparametric regression estimation for longitudinal data in models with martingale difference error's structure. Statistics (SCI期刊), 47(3),pp:521–534, 2013.
[6]. Zhou, X. C. & Lin, J. G.. On complete convergence for strong mixing sequences. Stochastics: An International Journal of Probability and Stochastic Processes (SCI期刊), 85(2), pp: 262–271, 2013.
[7] Yan,F.R., Huan Y., Liu,J.L., Lu,T. and Lin.J.G., Bayesian Inference for Generalized Linear Mixed Model Based on the Multivariate t Distribution in Population Pharmacokinetic Study, PLoS ONE(SCI期刊),, 8(3): e58369,2013.
[8] Tao,Y.X., Liu,L.J., Li,Z.H., Lin,J.G., Lu,T., Yan,F.R. Dose-Finding Based on Bivariate Efficacy-Toxicity Outcome Using Archimedean Copula. PLoS ONE(SCI期刊), 8(11): e78805.
[9] Zhou, X. C. & Lin, J. G.*. Empirical likelihood inference in mixtures of semiparametric varying coefficient EV models for longitudinal data with nonignorable dropout. Journal of the Korean Statistical Society(SCI期刊),42,pp:215-225,2013.
[10] Zhou, X. C. & Lin, J. G.. Asymptotic properties of wavelet estimators in semiparametric regression models under dependent errors. Journal of Multivariate Analysis(SCI期刊), 122 ,pp:251-270,2013.
[11] Zhou, X. C. & Lin, J. G.Yin,C.M..Asymptotic properties of wavelet-based estimator in nonparametric regression model with weakly dependent processes, Journal of Inequalities and Applications(SCI期刊), 2013:261,2013.
[12]. Chen,P., Dong,L.,Chen,W.Y. and Lin,J.G.*. Outlier Detection in Adaptive Functional- Coefficient Autoregressive Models Based on Extreme Value Theory. Mathematical Problems in Engineering(SCI期刊). 2013, Article ID 910828, 9 pages,2013.
2012年度
[1]. Lin,J.G*., Zhuang,Q.Y., Huang,C.. Fuzzy statistical analysis of multiple regression with crisp and fuzzy covariates and applications in analyzing economic data of china. Computational Economics (SCI, SSCI期刊), 39(1), pp:29-49, 2012.
[2]. Lin.J.G.*, Chen, J. and Li, Y. Bayesian analysis of student t linear regression with unknown change- point and application to stock data analysis. Computational Economics (SCI, SSCI期刊), 40, pp: 203 -217, 2012.
[3]. Lin,J. G.* & Qu, X. Y.. A consistent test for heteroscedasticity in semiparametric regression with nonparametric variance function based on the kernel method. Statistics (SCI期刊),46(5), pp:565- 576,2012.
[4]. Huang,C., Lin,J. G.* & Ren, Y. Y.. Statistical inferences for Pareto distribution based on interior penalty function algorithm and bootstrap methods and applications in analyzing stock data. Computational Economics (SCI, SSCI期刊),39(2),173-192, 2012.
[5]. Cao, C. Z., Lin, J. G. and Zhu, X. X.. On estimation of a heteroscedastic measurement error model under heavy-tailed distributions. Computational Statistics and Data Analysis (SCI期刊), 56(2), pp: 438-448, 2012.
[6]. Gao,Q. B. & Lin, J. G.*. Asymptotic properties of maximum quasi-likelihood estimators in generalized linear models with adaptive designs. Statistics (SCI期刊),46(6),pp:833-846, 2012.
[7]. Cao,C.Z. and Lin,J.G.. Heteroscedasticity and/or autocorrelation checks in longitudinal nonlinear mo-dels with elliptical and AR(1) errors. Acta Mathematicae Applicatae Sinica (SCI期刊),28(1),pp:49-62, 2012.
[8]. Gao, Q. B.. Lin, J. G.*, et al. Asymptotic properties of maximum quasi-likelihood estimators in generalized linear models with “working“ covariance matrix and adaptive designs. Communications in Statistics-Theroy and Methods (SCI期刊),41, pp:3544-3561, 2012.
[9]. Shi, A. J. and Lin, J. G.*. Tail dependence for regularly varying time series. Mathematical Problems in Engineering(SCI期刊), 2012, 280896, pp:1-14, 2012.
[10].Yang, Y., Lin, J. G. et al.. The finite-time ruin probability in two non-standard renewal risk models with constant interest rate and dependent subexponential claims. Journal of Kerean Statistical Society (SCI期刊),41, pp:213-224, 2012.
[11]. Zhao, H. X. and Lin, J. G.*. The large sample properties of the solutions of general estimating equations. J. Syst. Sci. Complex (SCI期刊), 25, pp:315-328, 2012.
[12]. Zhou, X. C. and Lin, J. G.. A wavelet estimator in a nonparametric regression model with repeated measurements under martingale difference error’s structure. Statistics and Probability Letters(SCI期刊),82, pp:1941-1922, 2012.
[13]. Wang, K. Y., Yang, Y. and Lin, J. G.. Precise large deviations for widely orthant dependent random variables with dominatedly varying tails. Front. Math. China(SCI期刊),7(5), pp:919-932,2012.
[14].Yan, F. R. & Lin, J. G.*. Empirical Likelihood Estimation for Population Pharmacokinetic Study Based on Generalized Linear Model. Journal of Applied Mathematics(SCI期刊), 2012, pp:1-13,2012.
2011年度
[1]. Lin,J.G.*,Zhu, L. X. et al.. Tests of heteroscedasticity and correlation in multivariate t regression models with AR and ARMA errors. Journal of Applied Statistics(SCI期刊),38(7), pp:1509-1531, 2011.
[2]. Yan, F. R., Lin, J. G.* and Liu, Y.. Sparse logistic regression for diagnosis of liver fibrosis in rat by using SCAD-penalized likelihood. Journal of Biomedicine and Biotechnology(SCI期刊),2011 (2011), pp:1-8, 2011.
[3]. Li,Y, Ni, Z. X. and Lin J. G.*. A stochastic simulation approach to model selection for stochastic volatility models. Communications in Statistics - Simulation and Computation (SCI期刊), 40 (7),1043-1056, 2011.
[4]. Zhou,X.C. and Lin,J.G.*. Complete moment convergence of moving average processes under ρ-mixing assumption. Mathematica Slovaca(SCI期刊),61(6),pp:979-992, 2011.
[5].Zhou,X.C. and Lin,J.G.*. On moments of the maximum of partial sums of moving average processes under dependence assumptions. Acta Mathematicae Applicatae Sinica (SCI期刊), 27 (4),pp:691-696,2011.
[6]. Cao, C. Z. & Lin, J. G.*. Diagnostics for elliptical linear mixed models with first-order autoregressive errors. Journal of Statistical Computation and Simulation(SCI期刊), 81(10), pp:1281-1296,2011 .
[7].Zhu, L. P., Qian, L. Y. & Lin, J. G.. Variable selection in a class of single-index models. Ann als of theInstitute of Statistical Mathematics(SCI期刊),63(6), pp: 1277-1293, 2011.
[8].Zhou, X. C and Lin, J. G.*. Strong consistency of estimators in partially linear models for longitudinal data with mixing-dependent structure. Journal of Inequalities and Applications(SCI期刊),2011, pp: 1-12, 2011.
[9] Yang,Y., Ma, X. and Lin,J.G.. Approximation for the Finite-Time Ruin Probability of a General Risk Model with Constant Interest Rate and Extended Negatively Dependent Heavy-Tailed Claims. Mathematical Problems in Engineering(SCI期刊)，2011, Article ID 852852, 14 pages，2011.
[10] Zou,X.C.,Tan,C.C. and Lin,J.G.. On the Strong Laws for Weighted Sums of ρ-Mixing Random Variables. Journal of Inequalities and Applications(SCI期刊). 2011, Article ID 157816, 8 pages,2011
2010年度
[1]. Lin J.G.*, Huang, C. & Zhuang, Q. Y.. Estimating generalized state density of near-extreme events and its applications in analyzing stock data. Insurance: Mathematics and Economics (SCI, SSCI期刊), 47, pp:13-20, 2010.
[2]. Chen,P., Li, L., Liu,Y. & Lin, J. G.*. Detection of outliers and patches in bilinear time series models. Mathematical Problems in Engineering(SCI期刊), 2010, pp:1-10, 2010.
[3]. Zhou, X. C. & Lin, J. G.*. On complete convergence for arrays of row-wise ρ-mixing random variables and Its Applications. Journal of Inequalities and Applications(SCI期刊), 2010, pp: 1-10, 2010.
[4]. Cao, C. Z., Lin, J. G.* & Zhu, L. X.. Heteroscedasticity and/or autocorrelation diagnostics in non-linear models with AR(1) and symmetrical errors. Statistical Papers(SCI期刊), 51(4), pp:813-836, 2010.
[5]. Xie, F. C., Lin, J.G. & Wei, B. C.. Influence analysis of additive mixed-effects nonlinear regression models via EM algorithm. Journal of Statistical Computation and Simulation (SCI期刊), 80(10), pp: 1115-1129, 2010.
[6]. Xie, F. C., Lin, J. G.,Wei, B. C.. Testing for varying zero-inflation and dispersion in generalized Poisson regression models. Journal of Applied Statistics(SCI期刊), 37(9), pp:1509-1522, 2010.
主要中文论著
[1]. 解锋昌、韦博成、林金官. 零过多数据的统计分析及其应用.科学出版社，2013.
[2]. 韦博成、林金官、解锋昌. 统计诊断. 高等教育出版社，2009.
