夏业茂 教 授

 教育经历：

   Ph.D. in Department of Statistics, The Chinese University of Hong Kong, HongKong, P.R. China,

   M.Sc. in Applied Statistics, Southeast University, Nanjing, Province P.R. China 1999

   B.Sc. in Mathematics, Anhui Normal University, Wuhu, P.R. China 1991

 工作经历：

    01. 2019 – present, Professor, Department of Applied Mathematics, Nanjing Forestry University, Nanijing, China

    01. 2014 –08.2019, Associate Professor, Department of Applied Mathematics, Nanjing Forestry University, Nanijing, China

    07. 2013 – 12.2013, Research Associate, Department of statistics, The Chinese University of Hong Kong, Hong Kong, China  

    08. 2007 -07. 2013, Associate Professor, Department of Applied Mathematics, Nanjing Forestry University, Nanijing, China

    10. 2005 - 08. 2007, Research Associate, Department of statistics, The Chinese University of Hong Kong, Hong Kong, China

  07. 1995 – 09. 1999, Lecture, Department of Mathematics and Statistics, Anhui Finanand Economic University, Bengbu, China

社会服务：

   江苏省概率统计学会常务理事，江苏省应用统计学会理事，国际泛华统计学会会士  

 《Mathematical Reviews》评论员，中国现场统计研究会多元分析应用专业委员会常务理事

 Selected Publications

1. Lee S Y*, Xia Y M (2006). Maximum likelihood methods in treating outliers and symmetrically heavy-tailed distributions for nonlinear structural equation models with missing data, Psychometrika, 71:565-585.

2. Lee S Y,* Xia Y M (2008). A robust bayesian approach for structural equation models with missing data. Psychometrika, 3: 343-364. 

3. Xia Y M, Song X Y*, Lee SY (2009). Robust model fitting for the non linear structural equation model under normal theory, British Journal of Mathematical and Statistical Psychology, 3: 529-568.

4. Song X Y*, Xia Y M, Lee SY (2009). Bayesian semiparametric analysis of structural equation models with mixed continuous and unordered categorical variables, Statistics in Medicine,17: 2253-2276.

5. Song X Y, Xia Y M, Pan J H and Lee, S Y (2011). Model comparison of Bayesian semiparametric and parametric structural equation models. Structural Equation Modeling - A Multidisciplinary Journal, 18: 55-72.

6. Xia Y M* and Liu, Y A and Fang Z (2010). Bayes analysis for generalized logistic  regression model and its application for Forestry survival rate. Journal of  Nanjing Forestry University, 34(2): 47-50.

7. Xia Y M* and Liu Y A (2010). Bayesian semiparametric analysis for generalized linear latent variable model. The proceedings of 2010 international conference on probability and statistics of the international institute for general systems studies. Advances on probability and statistics (Eds. by Jiang, Y and Wang, G Z), Vol 1: 308-312.

8. Liu Y A and Xia Y M* (2010). Testing of Heteroscedasticity in Partially Linear Autoregressive Models with Exogenous Variables. The proceedings of 2010 international conference on probability and statistics of the international institute for general systems studies. Advances on probability and statistics (Eds. by Jiang, Y and Wang, G Z), Vol.1, 313-316.

9. Xia Y M* and Liu, Y A (2011). Robust asymptotic inferences for mean covariance model. Chinese Journal of applied probability and statistics, 27(4): 399-409.

10. Hui X F, Liu Y A, Xia Y M (2011).The Forest Area Forecast Based on the Ensemble Kalman Filtering. Forest Inventory and Planning, 36(5): 1-5.

11. Xia Y M* and Liu, Y A (2014). Simulation study,  model selection and application for multivariate spatial latent variable model，Journal of Applied Statistics and Management, 33(5): 851-860.

12. Cheng Y S, Ding M W, Xia Y M, and Zhan W F (2014). Bayesian Analysis for dynamic generalized linear latent model with application to tree survival rate.Journal of Applied Mathematics,6:1-8.

13. Xia Y M* and Liu, Y A (2014). Robust Bayesian Analysis and Its Applications for Factor Analytic Model with Normal Scale Mixing. Chinese Journal of applied probability and statistics,30(4): 35-44.

14. Xia Y M*and Gou J W (2015). Assessing Heterogeneity of Multilevel Factor Analysis Model: A Semiparametic Approach, ACTA MATHEMATICAE APPLICATAE SINCA,38(4): 751-768.

15. Xia Y M*and Gou J W (2015). Estimation and Test for Dynamic Factor Analytic Model with Non-homogenous Structure,MATHEMATIC APPLICATA, 28(1): 65-73.

16. Xia Y M*, Gou J W and Liu Y A (2015). Semiparametric Bayesian Analysis for Factor Analysis Model Mixed with Hidden Markov Model, Applied Mathematics: A Journal of Chinese Universities (Ser.A) 2015,30(1): 17-30.

17. Xia Y M*and Gou J W (2016). Semi-parametric Bayesian Analysis for Latent Variable Models with Mixed Continuous and Ordinal Outcomes, Journal of Korean Statistics, 45(3): 451–465.

18. Xia Y M*, Tang N S and Gou J W (2016). Generalized Linear Latent Model for Multivariate Longitudinal Measurements Mixed with Hidden Markov Model. Journal of Multivariate analysis,152: 259-275.

19. Xia Y M* and Liu Y A (2016). Bayesian Semiparametric Analysis and Model Comparison for Confirmatory Factor Model,Chinese Journal of applied probability and statistics, 32(2): 157-183.

20. Xia Y M*(2016). Assessing Heterogeneity for Factor Analysis Model with Mixed Continuous and Ordinal Outcomes, Journal of Applied mathematics，421:1-12.

21. Xia Y M*, Chen G Y and Liu Y A (2016). Robust Inference on Hidden Markov Latent Variable Model. Journal of Systems Science and Mathematical sciences, 36(10):1783-1803.

22. Song X Y, Xia Y M and Zhu H T* (2017). Hidden Markov Latent Variable Models with Multivariate Longitudinal Data,Biometrics,73(1): 313-323.

23. Xia Y M* and Pan M L (2017). Bayesian Analysis for Confirmatory Factor Model with Finite Dimensional Dirichlet Prior Mixing. Commutation in Statistics: Simulation and Methods, 46(9): 4599-4619.

24. Xia Y M*, Gou J W (2017). A Note on Finite Dimensional Dirichlet prior. Commutation in Statistics: Simulation and Methods, 46(19): 9388-9396. 

25. Xia Y M*, Zeng X Qand Tang N S (2018). Bayesian Analysis for Hidden Markov Factor Analysis Models with Application to Cocaine Use Data. New insights into Bayesian inference. Eds. by Nezhad M S F. IntechOpen: London.

26. Xia Y M*, Lin Y B and Xiong S C (2018). Bayesian Inference on Two-Part Model. ATHEMATICA APPLICATA, 31(4):761-778.

27. Xia Y M*(2019). Bayesian Inference on Two-Part Mixture Model. ATHEMATICA  APPLICATA, 32(1):81-93.

28. Xia Y M* and Tang N S (2019). Bayesian Analysis for Mixture of Hidden Markov Latent Variable Models with Multivariate Longitudinal data. Computational Statistics and Data Analysis. 1(31): 741-765.

29. Xia Y M*, Lu B and Tang N S (2019). Inference on Two-part latent variable analysis model with multivariate longitudinal data. Structural equation modeling: A multidisciplinary Journal, 26(5):685-709.

30. Xia Y M*, Xiong S C and Tang N S (2019). Baysesian Semiparametric Analysis for Two-Part Latent Variable model. Communication in Mathematics and Statistics.DOI:10.1007/s40304-023-00359-1.

31. Xia Y M*, Liu Y A, Gou J W*(2022）Dirichlet Process and Its  Developments: A Survey. Front. Math. China. 17(1): 79–115.

32. Xia Y M*, Zhu Q H. Gou J W (2022). Assessing Heterogeneity of Two-Part Model via Bayesian Model Clustering with Its Application to Cocaine Use Data. Data Clustering. August 17, Eds. by Tang N S. IntechOpen: London.

33. Gou J W, Xia Y M*(2022). Identification of Latent Variable Model with Multiple Categorical Variables.ATHEMATICA  APPLICATA, 2:302-315

34. Gou J W, Xia Y M*, Jiang D P (2023). Bayesian Analysis of Two-Part Nonlinear  Latent Variable Model:Semiparametric Method. Statistical modeling,  23(4): 376–399.

35. Liao X L, Chen J Y, Zhang Q. Xia Y M*(2023). Variational Bayesian Inference for Two-Part Latent Variable Models. Journal of Systems Science and Mathematical sciences, 43(14) :1039-1068.

36. Chen J Y, Lin Z Y, Xia Y M* (2023).  Bayesian Analysis for Two-Part Latent Variable Model with Application to Fractional Data. Communication in Statistics: Theory and Methods. DOI:10.1080/03610926.2023.2273205.

37. Chen J Y, Yang C H, Xia Y M*(2023). Robust Model Fitting for Two-Part Model within Bayesian Semiparametric Framework: Variational Approach. REVSTAT-Statistical Journal. Accepted.

38. Yang C H, Liao X L, Xia Y M*(2024). Bayesian Inference on Generalized Cure Model.  ATHEMATICA  APPLI-CATA. 154:636-646.

39. Zhang Q; Zhang Y H; Xia* Y M (2024).  Bayesian Feature Extraction for Two-Part Latent Variable Model with Polytomous Manifestations.Mathematics,  12(5), 783.

40.  Xia Y M*, Chen J Y, Jiang D P (2024). Variational Bayesian analysis for general two-part latent variable model[J]. 

       Computional Statistics, 39: 2259–2290.

41. Kang Q, Xia Y M*(2024). Bayesian Inference on Two-Part Model with Missing Covariates.

      ATHEMATICA  APPLICATA, accepted.

42.Xia Y M*, Wang H Y, Kang Q (2024). Variational Bayesian Inference on Two-Part Quantiles. Model.  ATHEMATICA  APPLICATA, accepted.

教材： 《概率论与数理统计》 刘应安,夏业茂， 科学出版社，2013.

基金项目： 国家自然科学基金面上项目(主持,2015-2018，70万元，11471161，已结题)， 

       国家自然科学青年基金（参与，2017-2018，18万元，11501287，已结题）

       南京林业大学高学历人才项目(主持，2008,1万元，163101004,已结题)

       南京市留学回国人员科技择优资助项目(主持，2009-2011,3万元，013101001,已结题)

教改项目：南京林业大学“教学质量提升工程”《概率论》课程创新思维培养的实践 

指导学生: 

       1.江苏省优秀本科论文三等奖（张翰文）

       2.第五届全国应用统计专业学位研究生教育教育成果二等奖 （杨成慧）

       3.第五届全国应用统计专业学位研究生教育教育成果三等奖 （廖雪丽）

       4.江苏省应用统计学会2023年度优秀论文/案例一等奖（张琪）

       5.江苏省应用统计学会2024年度优秀论文一等奖（康晴） 

南京林业大学2010年度优秀教师

南京林业大学2019年度优秀教师

江苏省现场统计研究会第十一次学术年会优秀论文二等奖（2008） 

高等数学、概率论，线性代数，概率论与数理统计，多元统计分析，金融时间序列，数理统计、数理经济学