Welcome to Jinyuan Chang's Homepage
Dr. Jinyuan Chang
School of Statistics, Southwestern University of Finance and Economics
Area B, Tongbo Building, 555 Liutai Avenue,
Wenjiang District, Chengdu, Sichuan Province, China 611130
Email: changjinyuan [AT] swufe [DOT] edu [DOT] cn
I was born in Chongqing and raised in Chengdu, China. I had my senior middle school education at Chengdu No. 7 High School. Then, I attended School of Mathematical Science at Beijing Normal University in 2005 and got my Bachelor's degree of Science in Statistics in June 2009. Then, I went to Guanghua School of Management at Peking University for PhD study under the supervision of Prof. Song Xi Chen. I obtained the Doctor degree of Philosophy in Economics in July 2013. From September 2013 to Feburary 2017, I had a research fellow position in School of Mathematics & Statistics at the University of Melbourne under supervision of the late Prof. Peter Hall. Now, I am a Professor of Statistics and Econometrics at Southwestern University of Finance and Economics.
- High Dimensional Data Analysis
- Empirical Likelihood and Its Application
- Financial Econometrics
- Functional Data Analysis
- Associate Editor of Journal of the Royal Statistical Society Series B (2017.10 – Present)
- Associate Editor of Statistica Sinica (2017.08 – Present)
- American Statistical Association
- Institute of Mathematical Statistics
- International Chinese Statistical Association
- The Econometric Society
- Chang, J., Tang, C. Y. & Wu, T. T. (2018). A new scope of penalized empirical likelihood with high-dimensional estimating equations, The Annals of Statistics, in press.
- Chang, J., Guo, B. & Yao, Q. (2018). Principal component analysis for second-order stationary vector time series, The Annals of Statistics, in press. (Original title "Segmenting multiple time series by contemporaneous linear transformation: PCA for time series")
- Chang, J., Qiu, Y., Yao, Q. & Zou, T. (2018). Confidence regions for entries of a large precision matrix, Journal of Econometrics, Vol. 206, pp. 57–82. (Original title "On the statistical inference for large precision matrices with dependent data")
- Chang, J., Delaigle, A., Hall, P. & Tang, C. Y. (2018). A frequency domain analysis of the error distribution from noisy high-frequency data, Biometrika, Vol. 105, pp. 353–369.
- Chang, J., Zheng, C., Zhou, W.-X. & Zhou, W. (2017). Simulation-based hypothesis testing of high dimensional means under covariance heterogeneity, Biometrics, Vol. 73, pp. 1300–1310.
- Chang, J., Zhou, W., Zhou, W.-X. & Wang, L. (2017). Comparing large covariance matrices under weak conditions on the dependence structure and its application to gene clustering, Biometrics, Vol. 73, 31–41. (Original title "Bootstrap tests on high dimensional covariance matrices with applications to understanding gene clustering")
- Chang, J., Yao, Q. & Zhou, W. (2017). Testing for high-dimensional white noise using maximum cross-correlations, Biometrika, Vol. 104, pp. 111–127.
- Chang, J., Shao, Q.-M. & Zhou, W.-X. (2016). Cramer-type moderate deviations for Studentized two-sample U-statistics with applications, The Annals of Statistics, Vol. 44, pp. 1931–1956.
- Chang, J., Tang, C. Y. & Wu, Y. (2016). Local independence feature screening for nonparametric and semiparametric models by marginal empirical likelihood, The Annals of Statistics, Vol. 44, pp. 515–539.
- Chang, J., Guo, B. & Yao, Q. (2015). High dimensional stochastic regression with latent factors, endogeneity and nonlinearity, Journal of Econometrics, Vol. 189, pp. 297–312.
- Chang, J. & Hall, P. (2015). Double-bootstrap methods that use a single double-bootstrap simulation, Biometrika, Vol. 102, pp. 203–214.
- Chang, J., Chen, S. X. & Chen, X. (2015). High dimensional generalized empirical likelihood for moment restrictions with dependent data, Journal of Econometrics, Vol. 185, pp. 283–304.
- Chang, J., Tang, C. Y. & Wu, Y. (2013). Marginal empirical likelihood and sure independence feature screening, The Annals of Statistics, Vol. 41, pp. 2123–2148.
- Chang, J. & Chen, S. X. (2011). On the approximate maximum likelihood estimation for diffusion processes, The Annals of Statistics, Vol. 39, pp. 2820–2851.
Review Papers & Invited Discussion
- Chang, J., Guo, J. & Tang, C. Y. (2018). Peter Hall's contribution to empirical likelihood, Statistica Sinica, in press.
- Chang, J., Tang, C. Y. & Wu, T. T. (2017). High-dimensional statistical inferences with over-identification: confidence set estimation and specification test.
- Chang, J., Kolaczyk, E. D. & Yao, Q. (2018). Estimation of edge density in noisy networks.
Fellowships and Honors
- Selected Youth Scholar of the Chang Jiang Scholars Program of China, May 2018, Ministry of Education of the People's Republic of China
- Awardee of the Funds of Fok Ying-Tong Education Foundation for Young Teachers in the Higher Education Institutions of China, Feb. 2018, Fok Ying-Tong Education Foundation
- Selected Expert of National Thousand Youth Talent Plan, Feb. 2018, Organization Department of the CPC Central Committee
- IMS Travel Award, Jul. 2015, Institute of Mathematical Statistics
- IMS Travel Award, Jul. 2014, Institute of Mathematical Statistics
- Zhong Jia Qing Award, Oct. 2013, Chinese Mathematical Society
- Procter Gamble Award, May. 2013, Chinese Association of Probability and Statistics
- National Scholarship, Dec. 2012, Ministry of Education of the People’s Republic of China
- Laha Award, Jul. 2012, Institute of Mathematical Statistics
- National Scholarship, Nov. 2008, Ministry of Education of the People’s Republic of China
- Meritorious Winner of Mathematical Contest in Modeling, Mar. 2008, The Consortium for Mathematics and Its Applications, U.S.A.
- The First Prize of National High School Mathematics Contest, Dec. 2004, Chinese Mathematical Society