師資
蔣學(xué)軍，副教授。2009年獲香港中文大學(xué)統(tǒng)計(jì)學(xué)博士學(xué)位， 09年09月-10年10月在香港中文大學(xué)統(tǒng)計(jì)學(xué)系從事博士后研究，10年7月-13年6歷任中南財(cái)經(jīng)政法大學(xué)統(tǒng)計(jì)與數(shù)學(xué)學(xué)院講師、副教授、研究生導(dǎo)師。13年07月加入南方科技大學(xué)，獲國(guó)家自然科學(xué)基金（青年，面上）、廣東省自然科學(xué)基金(2項(xiàng))、深圳市科創(chuàng)委項(xiàng)目、深圳市技術(shù)委托開(kāi)發(fā)項(xiàng)目、廣東省本科高校金融學(xué)類教改項(xiàng)目等。主要科研方向?yàn)閿?shù)理統(tǒng)計(jì)、金融統(tǒng)計(jì)與計(jì)量，已發(fā)表SCI&SSCI期刊論文近40篇。
研究領(lǐng)域：
◆金融與計(jì)量經(jīng)濟(jì)統(tǒng)計(jì)
◆分位數(shù)回歸
◆高維數(shù)據(jù)降維
◆生存分析
◆貝葉斯分析
工作經(jīng)歷：
2019.07-present, 副教授，統(tǒng)計(jì)與數(shù)據(jù)科學(xué)系， 南方科技大學(xué)
2015.07-2019.06, Tenure-Track助理教授, 數(shù)學(xué)系，南方科技大學(xué)
2013.07-2015.06, Tenure-Track助理教授, 金融數(shù)學(xué)與金融工程系，南方科技大學(xué)
2011.09-2014.01, 班主任&指導(dǎo)教師，中南財(cái)經(jīng)政法大學(xué), 2011級(jí)EMBA深圳班
2011.10-2013.07 副教授&教研室主任, 碩士生導(dǎo)師，數(shù)理統(tǒng)計(jì)與金融統(tǒng)計(jì)系，中南財(cái)經(jīng)政法大學(xué)
2010.10-2011.09 講師, 數(shù)學(xué)與數(shù)量經(jīng)濟(jì)系，中南財(cái)經(jīng)政法大學(xué)
2009.09-2010.09 博士后, 香港中文大學(xué)統(tǒng)計(jì)學(xué)系
教育背景：
博士，香港中文大學(xué)，香港, 2009
碩士，云南大學(xué)，昆明, 2006
所獲榮譽(yù)：
○ 深圳市優(yōu)秀教師，2018
○ 南方科技大學(xué) “杰出教學(xué)獎(jiǎng)”，2018
○ 南方科技大學(xué) “優(yōu)秀導(dǎo)師獎(jiǎng)”，2016
○ 深圳市海外高層次人才“孔雀計(jì)劃”入選者
代表文章：
[1] Tan, F., Jiang. X., Guo, X. and Zhu, L. (2019). Testing heteroscedasticity for regression models based on projections. Statistica Sinica, online. [PDF]
[2] Guo, X., Jiang. X., Zhang, S. and Zhu, L. (2019). Pairwise distance-based heteroscedasticity for regressions. Science China- Mathematics, online.[PDF]
[3] Jiang, X., Fu, Y., Jiang, J., Li, J. (2019). Spatial Distribution of the Earthquake in Mainland China. Physica A: Staitsical Mechanics and its Application, online.[PDF]
[4] Jiang, X., Li, Y. , Yang, A. and Zhou, R. (2018). Bayesian semiparametric quantile regression modeling for estimating earthquake fatality risk. Empirical Economics, online.
[5] Lin, H., Jiang, X., Liang, H. and Zhang, W. (2018). Reduced rank modelling for functional regression with functional responses. Journal of multivariate analysis,169,205-217.
[6] Jiang, X. and Fu, Y. (2018). Measuring the Benefits of Development Strategy of “The 21st CenturyMaritime Silk Road” via Intervention Analysis Approach: Evidence from China and Neighboring Countries in Southeast Asian. Panoeconomicus,65(5)
[7] Xia, T., Jiang, J. and Jiang, X. (2018). Local influence for quasi-likelhood nonlinear models with random effects. Journal of Probability and Statistics. Vol 2018. 7.
[8] Li, J., Jiang, J., Jiang, X. and Liu, L.(2018). Risk-adjusted Monitoring of Surgical Performance. PLOSONE, 13(8), 1-13
[9] Zhao, W., Jiang, X. and Liang H. (2018). A Principal Varying-Coefficient Model for Quantile Regression: Joint Variable Selection and Dimension Reduction. Computational Statistics and Data Analysis,127, 269-280. (2018,11)
[10] Yang, A., Jiang, X., Shu, L., Lin, J. (2018). Sparse Bayesian Kernel Multinomial Probit Regression Model for High-dimensional Data Classification. Communication in statistics-theory and methods. Online
[11] Tian, G., Liu, Y., Tang, M. and Jiang, X. (2018). Type I multivariate zero-truncated/adjusted distributions with applications. Journal of computational and applied mathematics,344(15), 132-153.
[12] Jiang X., Guo, X., Zhang, N., Wang, B. and Zhang, B.* (2018). Robust multivariate nonparametric tests for detection of two- sample location shift in clinical trials. PLOSONE,13(4), 1-20.
[13] Yan A., Liang H., Jiang X. and Liu P. (2018). Sparse Bayesian variable selection for classifying high-dimensional data. Statistics and its interface,11(2), 385-395.
[14] Tian, G., Zhang, C. and Jiang, X. (2018). Valid statistical inference methods for a case-control study with missing data. Statistical Methods in Medical Research,27(4), 1001-1023.
[15] Xia T., Jiang X. and Wang X. (2018). Asymptotic properties of approximate maximum quasi-likelihood estimator in quasi- likelihood nonlinear models with random effects. Communication in Statistics,47, 1-12.
[16] Song, X. Kang, K. Ouyang, M., Jiang, X. and Cai. J. (2018). Bayesian Analysis of Semiparametric Hidden Markov Models with Latent Variables. Structural Equation Modeling: A Multidisciplinary Journal.25(1), 1-20.
[17] Li J., Liang, H., Jiang, X. and Song, X. (2018). Estimation and Testing for Time-varying Quantile Single-index Models with Longitudinal Data. Computational Statistics and Data Analysis,118, 66-83.
[18] Feng, K. and Jiang, X. (2017). Variational approach to shape derivatives for elasto-acousticcoupled scattering fields and an application with random interfaces. Journal of Mathematical Analysis and Application,456, 686-704.
[19] Jiang, J., Jiang. X., Li, J. Li, Y and Yan, W. (2017). Spatial Quantile Estimation of Multivariate Threshold Time Series Models. Physical A: Statistical Mechanics and Its Application,486,772-781.
[20] Guo, X., Jiang, X. and Wong, W. (2017). Stochastic Dominance and Omega Ratio: Measures to Examine Market Efficiency and Anomaly. Economies, 5(38),1-16.
[21] Tian, X., Jiang, X., and Wang, X. (2017). Diagnostics for quasi-likelihood nonliear models. Communication in Statistics-Theory and Methods,47(16), 8836-8851.
[22] Jiang, X., Tian, X. and Wang, X. (2017). Asymptotic properties of maximum quasi-likelihood estimator in quasi-likelihood nonlinear models with stochastic regression. Communication in Statistics-Theory and Methods,46(13), 6229-6239. 22.
[23] Niu, C. and Jiang, X. (2017). Statistical inference for a novel health inequality index. Theoretical Economics Letters,7, 251-262.
[24] Yang, A, Jiang, X., Xiang, L and Lin J. (2017). Sparse Bayesian Variable Selection in Multinomial Probit Regression Model with Application to High-dimensional Data Classification. Communication in Statistics-Theory and Methods.46(12), 6137-6150.
[25] Yang, A., Jiang, X., Shu, L. and Lin J. (2017). Bayesian Variable Selection with Sparse and Correlation Priors for High-dimensional Data Analysis. Computational Statistics,32, 127-143 .
[26] Huang, X., TIAN, G., Zhang, C. and Jiang, X. (2017). Type I multivariate zero-in?ated generalized Poisson distribution with applications. Statistics and Its Interface,10(2), 291-311.
[27] Yang, A., Jiang, X., Liu, P. and Lin J. (2016). Sparse bayesian multinomial probit regression model with correlation prior for High-dimensional data Classification. Statistics and probability letters,119,241-247.
[28] Jiang, X., Li, J., Xia, T and Wang, Y. (2016) Robust and efficient estimation with weighted composite quantile regression. Physical A: Statistical Mechanics and its Applications,457, 413-423.
[29] Jiang, X., Song, X. and Xiong, Z. (2016) Robust and efficient estimation of GARCH models. Journal of Testing and Evaluation,44(5), 1-23.
[30] Li, H., Tian, G., Jiang, X. and Tang, N. (2016). Testing hypothesis for a simple ordering in incomplete contingency tables. Computational Statistics and Data Analysis,99，25-37.
[31] Li, Y., Tang, N. and Jiang, X. (2016). Bayesian Approaches for Analyzing Earthquake Catastrophic Risk. Insurance: Mathematics and Economics, 68, 110-119.[JEPG]
[32] Xia, T., Jiang, X. and Wang, X. (2015). Strong consistency of the maximum quasi-likelihood estimator in quasi-likelihood nonlinear models with stochastic regression. Statistics & Probability letters,103, 37-45
[33] Xia, T., Wang, X. and Jiang, X. (2014). Asymptotic properties of maximum quasi-likelihood estimator in quasilikelihood nonlinear models with misspecified variance function. Statistics,48(4), 778-786.
[34] Song, X., Cai, J., Feng, X. and Jiang, X. (2014). Bayesian Analysis of Functional-Coefficient Autoregressive Heteroscedastic Model. Baysian Analaysis,9(2), P1-26.[PDF]
[35] Jiang, X., Tian, T. and Xie, D. (2014). Weighted type of quantile regression and its application. IMECS2014, II, 818-822.
[36] Jiang J, Jiang, X. and Song X(2014) Weighted composite quantile regression estimation of DTARCH models.The Econometrics Journal, 17(1)，1-23 [PDF]
[37] Jiang, X., Jiang, J. and Song, X. (2012.). Oracle model selection for nonlinear models based on weighted composite nonlinear quantile regression. Statistica Sinica,22(4), 1479-1506.[PDF]
[38] Jiang, J. and Jiang, X. (2011). Inference for partly linear additive COX models. Statistica Sinica,21(2)，901-921.[PDF]
[39] Jiang, X., Jiang, J. and Liu, Y. (2011). Nonparameteric regression under double-sampling designs. Journal of Systems Science and Complexity,24, 1-9.
[40] Xia, T., Wang, X. and Jiang, X. (2010). Asymptotic properties of the MLE in nonlinear reproductive dispersion models with stochastic regressors. Communication in Statistics,Theory and Methods,39, 2800-2810.
[41] Jiang, J., Marron, J.S. and Jiang, X.(2009). Robust Centroid Quantile Based Classification for High Dimension Low Sample Size Data. Journal of Statistical Planning and Inference,139(8), 2571-2580.
[42] Jiang, J., Zhou, H.,Jiang, X. and Peng, J. (2007). Generalized likelihood ratio tests for the structures of semiparametric additive models. TheCanadian Journal of Statistics,35(3), 381-398.
Publication (In Chinese)
1. (2016). 基于MCMC抽樣的金融貝葉斯半?yún)?shù)GARCH模型研究，數(shù)理統(tǒng)計(jì)與管理. To appear. 楊愛(ài)軍，蔣學(xué)軍，林金官，林曉星
2. (2006). The M-estimate of the local linear regression with variable bandwiths. Journal of Yunnan University, 28 (1), 12-15. 蔣學(xué)軍，夏天，唐年勝
科研項(xiàng)目：
國(guó)家自然科學(xué)基金面上項(xiàng)目，高維參數(shù)和半?yún)?shù)模型下似然推斷，項(xiàng)目編號(hào)11871263，55萬(wàn)，01/2019-12/2022，主持
國(guó)家自然科學(xué)基金青年項(xiàng)目，基于加權(quán)復(fù)合分位數(shù)回歸的雙門(mén)限ARCH，廣義ARCH, 及函數(shù)系數(shù)ARCH模型的推斷. 項(xiàng)目編號(hào):11101432, 21萬(wàn)，01/2012-04/2015, 主持
廣東省自然科學(xué)基金項(xiàng)目，廣東省艾滋病等重大流行病防治的動(dòng)態(tài)貝葉斯統(tǒng)計(jì)研究，項(xiàng)目編號(hào)2017A030313012，10萬(wàn)，2017/05-2020/05，主持
廣東省自然科學(xué)基金項(xiàng)目，計(jì)數(shù)數(shù)據(jù)模型選擇與統(tǒng)計(jì)診斷研究，項(xiàng)目編號(hào)2016A030313856, 經(jīng)費(fèi) 10 萬(wàn), 06/2016-06/2019, 主持
深圳市科創(chuàng)委項(xiàng)目，深圳市艾滋病流行情況風(fēng)險(xiǎn)預(yù)測(cè)及動(dòng)態(tài)防治的研究，項(xiàng)目編號(hào)JCYJ20170307110329106，經(jīng)費(fèi)30萬(wàn),06/2017.06-06/2019,主持
深圳市技術(shù)委托開(kāi)發(fā)項(xiàng)目，基于深度機(jī)器學(xué)習(xí)的量化交易系統(tǒng)， 項(xiàng)目編號(hào)：K1628Z015，經(jīng)費(fèi)20 萬(wàn)，08/2016-08/2018,主持