teresa

Pubilications

Semi/Nonparametric Regression

  • B-Splines Modal Estimation under Measurement Error with Deconvolution (2025+). The Canadian Journal of Statistics, forthcoming.
  • Robust Semi-Functional Censored Regression (2026). Journal of Multivariate Analysis, 211, 105491. [link]
  • Semiparametric Modal Regression with Varying Coefficients and Measurement Error (with A. Ullah, 2026). Journal of Statistical Planning and Inference, 240. [link]
  • Semi-Functional Varying Coefficient Mode-Based Regression (2025). Journal of Multivariate Analysis, 207, 105402. [link]
  • Nonparametric Estimator for Conditional Mode with Parametric Features (2024). Oxford Bulletin of Economics and Statistics, 86, 44-73. [link] [Wiley-Top Cited Article]
  • Semiparametric Partially Linear Varying Coefficient Modal Regression (with A. Ullah and W. Yao, 2023). Journal of Econometrics, 235, 1001-1026. [link]

Time Series and Dependence Modeling

  • Mode Meets Mean: A New Robust Volatility (2025+). Journal of Time Series Analysis. [link]
  • Kernel Mode-Based Varying Coefficient Models with Nonstationary Regressors (with W. Yao, 2025+). Journal of Nonparametric Statistics. [link]
  • Nonparametric Spatial Modeling towards the Mode (with W. Yao, 2025+). Statistica Sinica. [link]
  • Modal Volatility Function (with A. Ullah, 2025). Journal of Time Series Analysis, 46, 748-773. [link]
  • Parametric Modal Regression with Autocorrelated Error Process (2025). Statistica Sinica, 35, 457-478. [link]
  • Nonparametric Spatial Mode-Oriented Regression (with W. Yao, 2025). Electronic Journal of Statistics, 19, 4256-4311. [link]
  • Nonlinear Kernel Mode-Based Regression for Dependent Data (2024). Journal of Time Series Analysis, 45, 189-213. [link]
  • Nonlinear Modal Regression for Dependent Data with Application for Predicting COVID-19 (with A. Ullah and W. Yao, 2022). Journal of the Royal Statistical Society Series A, 185, 1424-1453. [link]

Machine/Statistical Learning

  • Online Kernel-Based Mode Learning (with W. Yao, 2025). Journal of Computational and Graphical Statistics, 34, 1498-1512. [link]
  • Optimal Subsampling for Functional Quasi-Mode Regression with Big Data (2025). Journal of Computational and Graphical Statistics, 34, 552-566. [link]
  • Distributed Learning for Kernel Mode-Based Regression (2025). The Canadian Journal of Statistics, 53, e11831. [link]

General Nonlinear Regression

  • Kernel Mode-Based Regression under Random Truncation (with W. Yao, 2024+). Statistica Sinica. [link]
  • Estimation and Testing of Forecast Rationality with Many Moments (with T.-H. Lee, 2025). Macroeconomic Dynamics, 29, e124. [link]
  • Mode-Adaptive Factor Models (2025). Scandinavian Journal of Statistics, 52, 1206-1238. [link]
  • Modal Regression for Fixed Effects Panel Data (with A. Ullah and W. Yao, 2021). Empirical Economics (Special Issue Honouring B. Baltagi), 60, 261-308. [link]

Working Papers

  • Envelope Kernel Mode-Based Regression, Reject and Resubmit (June, 2023)
  • Adaptive Robust Estimation for Varying Coefficient Models (with W. Yao), R&R (October, 2025)
  • Online Randomized Distributionally Robust Forecast Combination for Dependent Data, R&R (October, 2025)
  • Locally Misspecified Models with Robust Selection and Averaging, R&R (November, 2025)
  • Modal Regression Discontinuity Designs (with A. Ullah)
  • Penalized Particle Swarm Optimization for Mode Learning (with W. K. Wong and J. Zhou)
  • Doubly Debiased Robust Subsampling for Transfer Learning (with W. K. Wong)