Introduction to Professor Hongchang Hu
Full name: Hongchang Hu
Sex: Male
Professional Position: Professor
Final Education: PhD
Final Degree: PhD
Graduation School: Wuhan University
E-mail: retutome@163.com，Huhc6e8@hbnu.edu.cn
University Institution: School of Mathematics and Statistics, Hubei Normal University
Address: No.11,Cihu Road,Huangshi City, Hubei Province,P.R.China 435002
Research fields:Statistical inference and application of regression models, and time series analysis and its related fields.
Hongchang Hu, PhD, Professor, part-time master's supervisor at Central China Normal University, and director of the China Society of Engineering Probability and Statistics. The main research directions are statistical inference and its application of regression models, time series analysis, process statistics, etc.
I have successively led the National Natural Science Foundation of China's general projects, the Ministry of Education's key projects, the Hubei Provincial Department of Education's excellent young and middle-aged projects, and the Hubei Provincial Department of Education's key projects. As a major member, I have participated in research projects such as the National Natural Science Foundation of China (four projects), the Hubei Provincial Higher Education Excellent Young and Middle aged Science and Technology Innovation Team Support Project, and the Hubei Provincial Department of Education's major fund support project. I have successively authored one undergraduate and one graduate textbook, published one monograph at Science Press. I published nearly 100 papers in Journal of Mathematics (Chinese and English versions), Journal of Applied Mathematics (Chinese and English versions), Progress in Mathematics, Systems Science and Mathematics, Mathematical Yearbook (English version), Journal of Statistical Planning and Inference, Journal of Computational and Applied Mathematics, and so on, and more than 20 have been indexed by SCI.
t Publication of Academic Papers and Monographs: |
[1] Hongchang Hu, Li Wu. Convergence rates of wavelet estimators in semiparametric regression models under NA samples. Chinese Annals of Mathematics, Series B, 2012(SCI). [2] Esra Akdeniz Duran, Fikri Akdeniz, Hongchang Hu. Efficiency of a Liu-type estimator in semiparametric regression models, 3/3, Journal of Computational and Applied Mathematics, 2011 (SCI). [3] Hongchang Hu. Asymptotic normality of Huber–Dutter estimators in a linear model with AR(1) processes. Journal of Statistical Planning and Inference, 2013, 143: 548-562(SCI). [4] Hongchang Hu,Hengjian Cui, Kaican Li. Asymptotic properties of wavelet estimators in partially linear errors in variables models with long memory errors. Acta Mathematicae Applicatae Sinica, English, 2014(SCI). [5] Hongchang Hu, Lei Song. Quasi-Maximum likelihood estimators in GLM with AR. Acta Mathematica Sinica, English Series,2014(SCI). [6] Hongchang Hu, Yu Zhang, Xiong Pan. Asymptotic normality of DHD estimators in a partially linear model. Statistical Papers, 2016, 57:567-587 (SCI). [7] Zhen Zeng, Hongchang Hu(corresponding author). Weak linear representation of M-estimaton in GLMs with dependent errors. Stochastic and Dynamics, 2017 (SCI). [8] Hongchang Hu, Hengjian Cui, Kaican Li. Asymptotic properties of wavelet estimators in partially linear errors-in-variables models with long-memory errors. Acta Mathematicae Applicatae Sinica (English Series), 2018, 34(1): 77-96 (SCI). [9] Ting Cai, Hongchang Hu(corresponding author). Probability inequalities for sums of NSD random variables and applications. Communications in Statistics - Theory and Methods, 2020, 49(2):281-306 (SCI). [10] Hongchang Hu, Zhen Zeng. Penalized Lq-likelihood estimators and variable selection in linear regression models.Communications in Statistics - Theory and Methods, 2021 (SCI). [11] Hongchang Hu, Weifu Hu, Xinxin Yu.Pseudo-maximum likelihood estimators in linear regression models with fractional time series. Statistical Papers, 2021, 62:639-659 (SCI). [12] Yuli Li, Hongchang Hu(corresponding author). Sequential Lq-likelihood-ratio-type test. Chinese Journal of Contemporary Mathematics, 2023, 44(4): 1-20. [13] Hongchang Hu, Hengjian Cui, Yongsong Qin, Kaican Li. Modern Linear Regression Analysis Methods. Beijing: Science Press, 2013.(in Chinese) [14] Hongchang Hu, Yongsong Qin, Shouyou Huang. Statistical Inference of Dependent Linear Regression Models. Science Press, 2017.(in Chinese) |
t Research Project Situation: |
[1] Participate in Systematic Research on Semiparametric Estimation Theory and Its Application in Modern Surveying and Mapping, supported by the National Natural Science Foundation of China, from January 2003 to December 2006. [2] Participate in Exploration and Analysis of Biomathematical Models,funded by the Young and Middle aged Innovation Team of Hubei Provincial Department of Education,from May 2005 to December 2008. [3] Responsible for Estimation Theory and Application of Semi parametric Regression Model, Youth Project of Hubei Provincial Department of Education, 2006.01-2008.12 [4] Responsible for Theoretical Research and Application of Randomly Censored Statistical Models, Key Research Project of Hubei Provincial Department of Education, 2009.01-2011.12. [5] Responsible for Statistical Theory and Applications of Nonlinear Models, Key Funding Project for Science and Technology Research of the Ministry of Education, 2009.01-2011.12. [6] Participate in Robust variable selection and high-dimensional data analysis, National Natural Science Foundation of China project, January 2011-2013.12. [7] Responsible for Statistical Inference and Application of Dependent Regression Models and Diffusion Processes, sponsored by the National Natural Science Foundation of China from January 2015 to December 2018 [8] Participate in Variable selection and testing in high-dimensional sparse statistical models, National Natural Science Foundation of China, 2015.01-2018.12. |
t Lecture Courses： |
I have taught master's courses in Probability Theory and Mathematical Statistics, Advanced Mathematical Statistics, Regression Analysis, Time Series Analysis, Modern Statistical Methods, Stochastic Process Statistics, Diffusion Processes, and so on. |
