teresa

Pubilications

Semi/Nonparametric Regression

  • Wang, T. (2025+). Robust Semi-Functional Censored Regression. Journal of Multivariate Analysis, forthcoming.
  • Ullah, A. and Wang, T.* (2026). Semiparametric Modal Regression with Varying Coefficients and Measurement Error. Journal of Statistical Planning and Inference, 240, 106307. [link]
  • Wang, T. (2025). Semi-Functional Varying Coefficient Mode-Based Regression. Journal of Multivariate Analysis, 207, 105402. [link]
  • Wang, T. (2024). Nonparametric Estimator for Conditional Mode with Parametric Features. Oxford Bulletin of Economics and Statistics, 86 (1), 44-73. [link] [top cited-Wiley]
  • Ullah, A., Wang, T.*, and Yao, W. (2023). Semiparametric Partially Linear Varying Coefficient Modal Regression. Journal of Econometrics, 235 (2), 1001-1026. [link]

Time Series and Dependence Modeling

  • Wang, T.* and Yao, W. (2025+). Nonparametric Spatial Mode-Oriented Regression. Electronic Journal of Statistics, forthcoming.
  • Wang, T.* and Yao, W. (2025+). Kernel Mode-Based Varying Coefficient Models with Nonstationary Regressors. Journal of Nonparametric Statistics. [link]
  • Wang, T.* and Yao, W. (2025+). Nonparametric Spatial Modeling towards the Mode. Statistica Sinica. [link]
  • Ullah, A. and Wang, T.* (2025). Modal Volatility Function. Journal of Time Series Analysis, 46 (4), 748-773. [link]
  • Wang, T. (2025). Parametric Modal Regression with Autocorrelated Error Process. Statistica Sinica, 35, 457-478. [link]
  • Wang, T. (2024). Nonlinear Kernel Mode-Based Regression for Dependent Data. Journal of Time Series Analysis, 45 (2), 189-213. [link]
  • Ullah, A., Wang, T.*, and Yao, W. (2022). Nonlinear Modal Regression for Dependent Data with Application for Predicting COVID-19. Journal of the Royal Statistical Society Series A, 185 (3), 1424-1453. [link]

Machine/Statistical Learning

  • Wang, T.* and Yao, W. (2025+). Online Kernel-Based Mode Learning. Journal of Computational and Graphical Statistics. [link]
  • Wang, T. (2025). Optimal Subsampling for Functional Quasi-Mode Regression with Big Data. Journal of Computational and Graphical Statistics, 34 (2), 552-566. [link]
  • Wang, T. (2025). Distributed Learning for Kernel Mode-Based Regression. The Canadian Journal of Statistics, 53 (2), e11831. [link]

General Nonlinear Regression

  • Lee, T.-H. and Wang, T.* (2025+). Estimation and Testing of Forecast Rationality with Many Moments. Macroeconomic Dynamics. [link]
  • Wang, T.* and Yao, W. (2024+). Kernel Mode-Based Regression under Random Truncation. Statistica Sinica. [link]
  • Wang, T. (2025). Mode-Adaptive Factor Models. Scandinavian Journal of Statistics, 52 (3), 1206-1238. [link]
  • Ullah, A., Wang, T., and Yao, W. (2021). Modal Regression for Fixed Effects Panel Data. Empirical Economics (Special Issue on Honouring Badi Baltagi), 60 (1), 261-308. [link]

Working Papers

  • Envelope Kernel Mode-Based Regression, Reject and Resubmit (June, 2023)
  • Modal Regression Discontinuity Designs (with Aman Ullah)
  • Penalized Particle Swarm Optimization for Mode Learning (with Weng Kee Wong and Julie Zhou)
  • Doubly Debiased Robust Subsampling for Transfer Learning (with Weng Kee Wong)
  • Adaptive Robust Estimation for Varying Coefficient Models (with Weixin Yao)