xia qiang in scholat-z6尊龙旗舰厅

xia qiang

professor、associate dean

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个人简介

教授,博士生导师。2015年获中国人民大学统计学院博士学位,2006年至今在华南农业大学工作,现为数学与信息学院、软件学院副院长。近年来主持国家自然科学基金重大研究计划培育项目,国家自然科学基金面上项目,国家社科基金青年项目,教育部人文社科基金规划项目各1项。在国内外学术期刊发表论文30余篇,发表专著2部。担任美国数学评论评论员;担任中国商业统计会、中国现场统计研究会资源与环境,生存分析,大数据分析分会理事;担任广东省统计学会常务理事;广东省现场统计学会副理事长。电子邮箱:xiaqiang@scau.edu.cn

教育经历

2012/9–2015/6 中国人民大学统计学院, 统计学, 博士

2003/9–2006/6 华东师范大学统计系, 概率统计, 硕士

1993/9–1997/6 江苏师范大学(原徐州师范大学)数学系, 数学教育, 学士

工作背景

2018/12-至今  华南农业大学,数学与信息(软件)学院,教授

2015/1-2018/11  华南农业大学,数学与信息(软件)学院,副教授

2011/12-2014/12 华南农业大学,理学院,副教授

2006/7-2011/11 华南农业大学,理学院,讲师

1997/8-2003/8  江苏省徐州第七高级中学,中学教师

访问背景

2018/9-2019/6  东北师范大学,统计与数学学院,访问学者

2018/7-2018/8  香港大学,统计与精算系,research associate

2016/12-2017/12 美国德州农工大学,统计系,国家公派访问学者

2015/7-2015/8  香港理工大学,应用数学系,research associate

2013/11-2014/2  香港浸会大学,数学系,访问学人(王宽诚教育基金会和香港浸会大学合办的中国内地访问学人计划)

2013/7-2013/8  香港理工大学,应用数学系,research associate

授课课程

高等数理统计;时间序列分析;回归分析;多元统计分析;非参数统计;数理统计;统计计算

已发表科研论文

#学生,* 通讯作者

[22] qiang xia, xianyang zhang*, adaptive testing for alphas in high dimensional factor pricing models, journal of business & economic statistics statistics. 2023 (ssci&sci, 已接收)

[21] jun yang#, renjie wu#, qiang xia, jingjing yu, lingxian yi, ying huang, meixin deng, wanyun he, yuman bai, luchao lv, vincent burrus, chengzhen wang, and jian-hua liu*,  the evolution of infectious transmission promotes the persistence of mcr-1 plasmids,  mbio. 2023 (sci, 已接收, 共同一作)

[20]  rubing liang, binbin qin, qiang xia*, bayesian inference for mixed gaussian garch-type model by hamiltonian monte carlo algorithm, computational economics. 2022 (ssci&sci, 已接收, 通讯作者)

[19]  xiaobing zheng#, qiang xia*, rubing liang, bayesian inference for order determination of double threshold variables autoregressive models, studies in nonlinear dynamics & econometrics. 2022 (ssci, 已接收, 通讯作者)

[18] jinshan liu, jiazhu pan, qiang xia*, li xiao, on determination of the number of factors in an approximate factor model,  studies in nonlinear dynamics & econometrics. 2022 (ssci, 已接收,通讯作者)

[17] qiang xia, heung wong,  shirun shen, kejun he*, factor analysis for high dimensional time series: consistent estimation and efficient computation, statistics analysis and data mining. 2022, 15(2): 247 -263  (sci)

[16] xiaobing zheng#, kun liang, qiang xia*, dabing zhang, best subset selection for double-threshold-variable autoregressive moving-average models: the bayesian approach.  computational  economics, 2022, 59:1175-1201 (ssci&sci,通讯作者)

[15] jinshan liu, jiazhu pan, qiang xia*, ying xiao, subset selection of double-threshold moving average models through the application of the bayesian method, statistics and its interface. 2022, 15: 51-61(sci,通讯作者)

[14] jinshan liu, qiang xia*. some finite sample results for a system of seemingly unrelated regression equations, communications in statistics - theory and methods, 2022, 11(51):3629-3644 (sci,通讯作者)

[13] qiang xia*, zhiqiang zhang, wai keung li. a portmanteau test for smooth transition autoregressive models,  journal of time series analysis, 2020, 41: 722–730 .  (sci)

[12] qiang xia, rubing liang*, jianhong wu, heung wong.  determining the number of factors for high-dimensional time series,  statistics and its interface, 2018, 11: 307-316. (sci)

[11]  shuxia ni#, qiang xia*, jinshan liu. bayesian subset selection for two-threshold variable autoregressive models, studies in nonlinear dynamics & econometrics, 2018, 22, 4:1-16. (ssci,通讯作者)

[10] qiang xia*, kejun he, cunzhen niu. a model adaptive test for parametric single index time series model, journal of time series analysis, 2017, 38(6):981-999. (sci)

[9] qiang xia, rubing liang*, jianhong wu, transformed contribution ratio test for the number of factors in static approximate factor models, computational statistics and data analysis, 2017, 112:235-241. (sci)

[8] rubing liang, qiang xia*, jiazhu pan, jinshan liu, testing a linear arma model against threshold-arma models: a bayesian approach, communications in statistics - simulation and computation, 2017, 46: 1302-1317. (sci,通讯作者) 

[7]  qiang xia, heung wong*, jinshan liu,rubing liang, bayesian analysis of power-transformed and threshold garch models: a griddy-gibbs sampler approach, computational economics, 2017, 50(3): 353–372. (ssci&sci)

[6] qiang xia, wangli xu, lixing zhu*, consistently determining the number of factors in multivariate volatility modelling, statistica sinica, 2015, 25: 1025-1044. (sci)

[5]  rubing liang, cuizhen niu, qiang xia*, zhiqiang zhang, nonlinearity testing and modeling for threshold moving average models, journal of applied statistics, 2015, 42: 2614-2630. (sci,通讯作者)

[4] qiang xia, rubing liang, jinshan liu*, a bayesian analysis of autoregressive models with exogenous variables and power-transformed and threshold garch errors, communications in statistics - theory and methods, 2015, 44: 1967-1980. (sci)

[3] qiang xia, jinshan liu*, jiazhu pan, rubing liang, bayesian analysis of two-regime threshold autoregressive moving average model with exogenous inputs, communications in statistics - theory and methods, 2012, 41: 1089-1104. (sci)

[2] qiang xia, jiazhu pan, zhiqiang zhang, jinshan liu*, a bayesian nonlinearity test for threshold moving average models, journal of time series analysis, 2010, 31: 329-336. (sci)

[1]  夏强,梁茹冰,李高荣*,参数单指标分位数自回归模型的诊断检验,中国科学--数学,2019 , 49 (6): 879 -898.

专著

[2]  刘金山,夏强,基于mcmc算法的贝叶斯统计方法,科学出版社,420000,2016.

[1]  qiang xia, heung wong, identification of threshold autoregressive moving average models, springer-verlag new york, 8500, 2016.

教材

[1] 夏强,刘金山,概率论与数理统计,人民邮电出版社,380000,2018.

主持课题

7. 国家自然科学基金面上项目,近似因子模型的高维稀疏截距向量检验问题的若干研究(12171161),2022.1-2025.12,在研;

6. 国家自然科学基金重大研究计划培育项目,高维时间序列因子自回归模型的统计推断及应用研究(91746102),2018.1-2020.12,已结题;

5. 教育部人文社科基金规划项目,高维时间序列静态的近似因子模型的因子个数估计理论及 应用研究(17yja910002),2017.7-2020.7,已结题;

4. 广东省自然科学基金面上项目,高维数据中因子模型的统计推断及应用 (2016a030313414),2016/6-2019/6,已结题;

3. 全国统计科学研究重点项目,高维时间序列因子模型的统计推断方法的改进及应用研究(2015lz48),2015/12-2017/11,已结题;

2. 国家社会科学基金青年项目,两类门限型计量经济学模型的贝叶斯检验及应用研究(2ctj0191),2012/09-2015/08,已结题;

1. 教育部人文社科基金青年项目,ptgarch模型的贝叶斯检验及其在经济金融波动问题中的应用(11yjczh195),2011.8-2014.8,已结题;

 

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