| Model-free time-aggregated predictions for econometric datasets K Wu, S Karmakar Forecasting 3 (4), 920-933, 2021 | 9 | 2021 |
| A model-free approach to do long-term volatility forecasting and its variants K Wu, S Karmakar Financial Innovation 9 (1), 1-38, 2023 | 7 | 2023 |
| Bootstrap prediction inference of nonlinear autoregressive models K Wu, DN Politis Journal of Time Series Analysis, 2024 | 5 | 2024 |
| Scalable Subsampling Inference for Deep Neural Networks K Wu, DN Politis arXiv preprint arXiv:2405.08276, 2024 | 1 | 2024 |
| GARHCX-NoVaS: A Model-free Approach to Incorporate Exogenous Variables K Wu, S Karmakar arXiv preprint arXiv:2308.13346, 2023 | 1 | 2023 |
| Multi-Step-Ahead Prediction Intervals for Nonparametric Autoregressions via Bootstrap: Consistency, Debiasing, and Pertinence DN Politis, K Wu Stats 6 (3), 839-867, 2023 | 1 | 2023 |
| Deep Limit Model-free Prediction in Regression K Wu, DN Politis arXiv preprint arXiv:2408.09532, 2024 | | 2024 |
| Determining Timing Effects of Microrandomized Trials Using Intensive Longitudinal Data and the Differential Time-Varying Effect Model K Wu, JR McFadden, NC Jacobson PsyArXiv, 2020 | | 2020 |
| Online Supplement for “Bootstrap Prediction Inference of Non-linear Autoregressive Models” K Wu, DN Politis | | |
