Zhaoxing Gao

Zhaoxing Gao

Statistician and Data Scientist

Publications

You can also find my articles on my Google Scholar profile.

Journal Articles (Students Advised)
  1. Fang, P., Gao, Z., and Tsay, R.S. (2025+). Determination Of The Effective Cointegration Rank In High-dimensional Time-series Predictive Regressions. Journal of Business & Economic Statistics. Forthcoming.
  2. Jiang, H., Shen, B., Li, Yu. and Gao, Z. (2025+). Regularized Estimation of High-Dimensional Matrix-Variate Autoregressive Models. Statistica Sinica. Forthcoming. [Link]
  3. Gao, Z., and Tsay, R.S. (2025+). Denoising and Multilinear Projected-Estimation of High-Dimensional Matrix-Variate Factor Time Series. IEEE Transactions on Information Theory. Forthcoming. [Link]
  4. Gao, Z., and Tsay, R.S. (2024+). Supervised Dynamic PCA: Linear Dynamic Forecasting with Many Predictors. Journal of the American Statistical Association. Forthcoming. [Link]
  5. Gao, Z., and Tsay, R.S. (2023). Divide-and-Conquer: A Distributed Hierarchical Factor Approach to Modeling Large-Scale Time Series Data. Journal of the American Statistical Association, 118(544), 2698-2711. [Link]
  6. Gao, Z., Mi, Z., and Ling, S. (2023). Testing threshold effect in single-index models. Statistics and Its Interface, 16(1), 43-56. [Link]
  7. Gao, Z. and Tsay, R. S. (2023). A two-way transformed factor model for matrix-variate time series. Econometrics and Statistics, 27, 83--101. [Link]
  8. Gao, Z. and Tsay, R. S. (2022). Modeling high-dimensional time series: a factor model with dynamically dependent factors and diverging eigenvalues. Journal of the American Statistical Association, 117(539), 1398-1414. [Link]
  9. Gao, Z. and Tsay, R. S. (2021). Modeling high-dimensional unit-root time series. International Journal of Forecasting， 37(4), 1535-1555.[Link]
  10. Gao, Z., Ma, Y., Wang, H. and Yao, Q. (2019). Banded spatio-temporal autoregressions. Journal of Econometrics, 208(1), 211–230. [Link]
  11. Gao, Z. and Tsay, R. S. (2019). A structural-factor approach for modeling high-dimensional time series and space-time data. Journal of Time Series Analysis, 40, 343–362. [Link]
  12. Gao, Z., and Ling, S. (2019). Statistical inference for structurally changed threshold autoregressive models. Statistica Sinica, 29(4), 1803–1829. [Link]
  13. Gao, Z., Ling, S., and Tong, H. (2018). Tests for TAR models vs. STAR models–a separate family of hypotheses approach. Statistica Sinica, 28(4), 2857–2883. [Link]
  14. Wu, Z., Chen, X., and Gao, Z. (2023). Bayesian Non-parametric Method for Decision Support: Forecasting Online Product Sales. Decision Support Systems, 174, 114019 [Link]
  15. Fang, P., Gao, Z., and Tsay, R.S. (2023). Supervised Kernel Principal Component Analysis for Forecasting. Finance Research Letters, 58, 104292 [Link]