姓名 | 性别 | 男 | 民族 | 汉 |
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出生年月 | 1980.12 | 政治面貌 | 中共党员 | |||||
职称（硕导、博导） | 副教授（硕导） | 职务 | 应用统计（专硕）负责人 统计学学科秘书 | |||||
联系电话 |
| ggb11111111@163.com | ||||||
学习工作简历 | 2012.07-至今 山东理工大学 数学与统计学院 2002.09-2004.07 曲阜师范大学 数学学院，数学专业学士 2004.09-2007.07 厦门大学 数学学院，概率论与数理统计专业硕士 2009.09-2012.06 山东大学 金融研究院，概率论与数理统计专业博士 2013.11-2016.09 山东大学 金融研究院， 博士后 | |||||||
社会兼职 | 2014- 美国《Mathematical Reviews》评论员 2020-中国商业统计学会理事 | |||||||
教授课程 |
研究生课程：高等数理统计、回归分析、计算统计等。 本科生课程：统计学、统计计算、非参数统计、大数据统计分析、数据分析与软件、概率论与数理统计、线性代数、高等代数等。 | |||||||
主要研究方向 |
大数据统计计算、 金融统计、 工业统计。 研究领域：分布式推断理论及应用、分布式抽样理论、分布式MCMC、深度学习算法。 | |||||||
部分科研项目 |
1、基于计算密集型方法的动态广义线性模型研究 国家自然科学基金2014/01-2014/12 NSFC 11326183 2、基于并行MCMC的动态金融数据分析 中国博士后基金面上项目 2014-2015 CPSF 2014M551888 3、基于并行统计计算的大数据分析, 山东省自然科学基金面上项目, 2016 -2019, ZR2016AM09 4、基于分布式统计推断的大数据理论研究, 山东省自然科学基金面上项目, 2020-2023, ZR2020MA022. | |||||||
部分科研成果
| 19] Guangbao Guo, Guoqi Qian, Lu Lin and Wei Shao (2021). Parallel inference for big data with the group bayesian method. Metrika(1). DOI:10.1007/s00184-020-00784-0. (SCI, IF: 0.679) [18] Guangbao Guo and Weidong Zhao (2021). Schwarz method for financial engineering. Journal of Computational Mathematics. DOI:10.4208/jcm.2003-m2018-0115. (SCI,T1) [17] Guangbao Guo (2021). Taylor quasi-likelihood for limited generalized linear models. Journal of Applied Statistics, 1-24. DOI: 10.1080/02664763.2020.1743650. (SCI, IF: 1.031) [16] Guangbao Guo, Yue Sun, Xuejun Jiang. (2020). A partitioned quasi-likelihood for distributed statistical inference. Computational Statistics, 35(4), 1577-1596. (SCI, IF: 0.744) [15] Guangbao Guo (2020). A block bootstrap for quasi-likelihood in sparse functional data. Statistics: A Journal of Theoretical and Applied Statistics,54(5), 909-925. (SCI, IF: 0.645) [14] Guangbao Guo, James Allison and Lixing Zhu. (2019). Bootstrap maximum likelihood for quasi-stationary distributions. Journal of Nonparametric Statistics, 31(1), 64-87.(SCI, IF: 0.607) [13]Wenjie You, Zijiang Yang, Guangbao Guo, Xiu-Feng Wan, Guoli Ji (2018). Prediction of DNA-binding proteins by interaction fusion feature representation and selective ensemble. Knowledge-Based Systems, 163,598-610.(SCI, IF: 5.921) [12] Guangbao Guo (2018). Finite difference methods for the BSDEs in finance. International Journal of Financial Studies, 6(1), 1-15. (Review) [11] Shao, W. and Guo, G. (2018). Multiple-try simulated annealing algorithm for global optimization. Mathematical Problems in Engineering, 2018(1), 1-11. (SCI, IF: 1.009) [10] Guangbao Guo, Wenjie You, Lu Lin and Guoqi Qian. (2016). Covariance Matrix and Transfer Function of Dynamic Generalized Linear Models. Journal of Computational and Applied Mathematics. 296, 613–624. (SCI, IF: 2.037) [9] Guangbao Guo, Wei Shao, Lu Lin and Xuehu Zhu. (2016). Parallel Tempering for Dynamic Generalized Linear Models. Commun.Statist.-Theory Meth. 45, 6299-6310. (SCI, IF: 0.531) [8] Guangbao Guo, Lin, Lu. (2016). Parallel Bootstrap and Optimal Subsample Lengths in Smooth Function Models. Communications in Statistics– Simulation and Computation, 45(6), 2208-2231. (SCI, IF: 0.651) [7] Guangbao Guo, Wenjie You and Guoqi Qian.(2015). Parallel Maximum Likelihood Estimator for Multiple Linear Regression Models. Journal of Computational and Applied Mathematics. 273, 251-263. (SCI, IF: 2.037) [6] Guangbao, Guo and Xiangyun Lin. (2014). Nonlinear Markov Chains and G-Brownian Motion. Journal of Probability and Statistical Science. 12, 59-68. (Big-g) [5] Wei Shao, Guangbao Guo*, Guoqing Zhao and Fanyu Meng.(2014) Simulated annealing for the bounds of Kendall’s and Spearman’s , Journal of Statistical Computation and Simulation. 84(12), 2688-2699. (SCI, IF: 0.918) [4] Wei Shao, Guangbao Guo, Fanyu Meng and Shuqin Jia. (2012). An efficient proposal distribution for Metropolis–Hastings using a-splines technique. Computational Statistics and Data Analysis, 57, 465-478. (SCI, IF: 1.186) [3] Guangbao, Guo and Weidong, Zhao. (2012).Schwarz Methods for Quasi Stationary Distributions of Markov Chains. Calcolo, 49, 21-39. (SCI, IF: 1.521) [2] Guangbao,Guo. (2012).Parallel Statistical Computing for Statistical Inference. Journal of Statistical Theory and Practice. 6, 536-565. (Review) [1] Guangbao, Guo and Shaoling, Lin. (2010). Schwarz Method for Penalized Quasilikelihood in Generalized Additive Models. Commun. Statist.-Theory Meth., 39, 1847-1854. (SCI, IF: 0.612) | |||||||
部分学术报告
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1,Parallel Gibbs variable selection for high-dimensional generalized linear models, CFE-CMStatistics 2018: 11th International Conference of the ERCIM WG on Computational and Methodological Statistics, University of Pisa, Italy. 2,Hypergeometric-type bootstrap quasi-likelihood for functional longitudinal data: Inference and applications, CFE-CMStatistics 2017: 10th International Conference of the ERCIM WG on Computational and Methodological Statistics, London. 3,Adaptive FPCA for functional generalized linear models，IMS-APRM 2016: The 4th Institute of Mathematical Statistics, Asia Pacific RimMeeting， 2016 , Hong Kong. 4,Bootstrap quasi likelihood for functional longitudinal data, IASC ARS 2015: 9th Asian Regional Section of Statistical Computing Conference, 2015, Singapore. 5,Parallel statistical computing for dynamic generalized linear models, 2015 IMS-China: International Conference on Statistics and Probability, Kunming. 6,Bootstrap for quasi stationary distributions，The 24th International Workshopon Matrices and Statistics，2015，Haikou. 7,Schwarz methods for second order BSDEs in finance, The announcement of 7th symposium on BSDEs, 2014, Weihai. | |||||||
