Publications
Semi/Nonparametric Regression
- Adaptive Robust Estimation for Varying Coefficient Models (with Weixin Yao, 2026+). Computational Statistics & Data Analysis. [link]
- B-Splines Modal Estimation under Measurement Error with Deconvolution (2026+). The Canadian Journal of Statistics. [link]
- Kernel Mode-Based Varying Coefficient Models with Nonstationary Regressors (with Weixin Yao, 2025+). Journal of Nonparametric Statistics. [link]
- Nonparametric Spatial Modeling towards the Mode (with Weixin Yao, 2027). Statistica Sinica, 37. [link]
- Robust Semi-Functional Censored Regression (2026). Journal of Multivariate Analysis, 211, 105491. [link]
- Kernel Mode-Based Regression under Random Truncation (with Weixin Yao, 2026). Statistica Sinica, 36. [link]
-
Semiparametric Modal Regression with Varying Coefficients and Measurement Error (with Aman Ullah, 2026).
Journal of Statistical Planning and Inference, 240. [link]
- Nonparametric Spatial Mode-Oriented Regression (with Weixin Yao, 2025). Electronic Journal of Statistics, 19, 4256-4311. [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 Aman Ullah and Weixin Yao, 2023). Journal of Econometrics, 235, 1001-1026. [link]
Time Series and Dependence Modeling
- On Robust Estimation for Moderate Deviations from a Unit Root (2026+). TEST, forthcoming.
- Online Randomized Distributionally Robust Forecast Combination for Dependent Data (2026+). Journal of Time Series Analysis. [link]
- Testing Distributional Granger Causality with Entropic Optimal Transport (2026+). Journal of Time Series Analysis. [link]
- Mode Meets Mean: A New Robust Volatility (2025+). Journal of Time Series Analysis. [link]
- Modal Volatility Function (with Aman 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]
- 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 Aman Ullah and Weixin Yao, 2022). Journal of the Royal Statistical Society Series A, 185, 1424-1453. [link]
Machine/Statistical Learning
- Geometry-Misalignment in Distributional Learning (with Xiaoting Zhong, 2026+). International Conference on Machine Learning (ICML), forthcoming.
- Doubly Debiased Robust Subsampling for Transfer Learning (with Weng Kee Wong, 2026). Journal of Machine Learning Research, 27, 1-53.
- Online Kernel-Based Mode Learning (with Weixin 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]
- A Machine Learning Strategy for Autism Screening in Toddlers (with Luke E. K. Achenie, Angela Scarpa, Reina S. Factor, Diana L. Robins, and D. Scott McCrickard, 2019). Journal of Developmental & Behavioral Pediatrics, 40, 369-376. [link]
Other Models and Methods
- Estimation and Testing of Forecast Rationality with Many Moments (with Tae-Hwy 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 Aman Ullah and Weixin Yao, 2021). Empirical Economics (Special Issue Honouring B. Baltagi), 60, 261-308. [link]
Working Papers
- Graph Neural Item Response Model for Networked Learning Environments (with Xiaoting Zhong). Journal of Educational and Behavioral Statistics, Conditional Acceptance (May, 2026).
- Envelope Kernel Mode-Based Regression, Reject and Resubmit (June, 2023)
- Locally Misspecified Models with Robust Selection and Averaging, under revision (November, 2025)
- Evidence-Driven Ambiguity Sets for Robust Optimization with E-Values, under revision (January, 2026)
- Deep ReQU Mode-Informed Learning for Global Temperature Forecasting (with Vasco J. Gabriel), under revision (March, 2026)
- Modal Regression Discontinuity Designs (with Aman Ullah)
- Penalized Particle Swarm Optimization for Mode Learning (with Weng Kee Wong and Julia Zhou)