| Non-parametric hybrid models for wind speed forecasting Q Han, F Meng, T Hu, F Chu Energy Conversion and Management 148, 554-568, 2017 | 116 | 2017 |
| A sieve semiparametric maximum likelihood approach for regression analysis of bivariate interval-censored failure time data Q Zhou, T Hu, J Sun Journal of the American Statistical Association 112 (518), 664-672, 2017 | 95 | 2017 |
| Adaptive Semi-varying Coefficient Model Selection T Hu, Y Xia Statistica Sinica 22 (2), 575-599, 2012 | 88 | 2012 |
| Sieve maximum likelihood regression analysis of dependent current status data L Ma, T Hu, J Sun Biometrika 102 (3), 731-738, 2015 | 85 | 2015 |
| Non-parametric models for joint probabilistic distributions of wind speed and direction data Q Han, Z Hao, T Hu, F Chu Renewable Energy 126, 1032-1042, 2018 | 57 | 2018 |
| Regression analysis of informative current status data with the additive hazards model S Zhao, T Hu, L Ma, P Wang, J Sun Lifetime data analysis 21, 241-258, 2015 | 39 | 2015 |
| Efficient estimation for semiparametric cure models with interval-censored data T Hu, L Xiang Journal of Multivariate Analysis 121, 139-151, 2013 | 35 | 2013 |
| Regression analysis of bivariate current status data under the proportional hazards model T Hu, Q Zhou, J Sun Canadian Journal of Statistics 45 (4), 410-424, 2017 | 32 | 2017 |
| Regression analysis of current status data in the presence of dependent censoring with applications to tumorigenicity experiments S Li, T Hu, P Wang, J Sun Computational statistics & data analysis 110, 75-86, 2017 | 30 | 2017 |
| Short-term wind speed forecasting based on signal decomposing algorithm and hybrid linear/nonlinear models Q Han, H Wu, T Hu, F Chu Energies 11 (11), 2976, 2018 | 26 | 2018 |
| Regression analysis of current status data in the presence of a cured subgroup and dependent censoring Y Liu, T Hu, J Sun Lifetime data analysis 23, 626-650, 2017 | 22 | 2017 |
| Partially linear transformation cure models for interval-censored data T Hu, L Xiang Computational statistics & data analysis 93, 257-269, 2016 | 22 | 2016 |
| Cox regression analysis of dependent interval-censored failure time data L Ma, T Hu, J Sun Computational statistics & data analysis 103, 79-90, 2016 | 21 | 2016 |
| Drought prediction based on feature-based transfer learning and time series imaging W Tian, J Wu, H Cui, T Hu IEEE Access 9, 101454-101468, 2021 | 20 | 2021 |
| Tests for Coefficients in High-dimensional Additive Hazard Models P Zhong, T Hu, J Li Scandinavian Journal of Statistics 42 (3), 649-664, 2015 | 14 | 2015 |
| A class of semiparametric transformation cure models for interval-censored failure time data S Li, T Hu, X Zhao, J Sun Computational statistics & data analysis 133, 153-165, 2019 | 11 | 2019 |
| Active greeting technique: a mother-and-child catheter based technique to facilitate retrograde wire externalization in recanalization of coronary chronic total occlusion J Ge, L Ge, B Zhang, X Zhong, J Ma, L Ru, T Hu, J Qian Science bulletin 63 (23), 1565-1569, 2018 | 11 | 2018 |
| Variable selection for generalized odds rate mixture cure models with interval-censored failure time data Y Xu, S Zhao, T Hu, J Sun Computational statistics & data analysis 156, 107115, 2021 | 10 | 2021 |
| Generalization bounds of multitask learning from perspective of vector-valued function learning C Zhang, D Tao, T Hu, B Liu IEEE Transactions on Neural Networks and Learning Systems 32 (5), 1906-1919, 2020 | 10 | 2020 |
| Regression analysis of informative current status data with the semiparametric linear transformation model D Xu, S Zhao, T Hu, M Yu, J Sun Journal of Applied Statistics 46 (2), 187-202, 2019 | 10 | 2019 |
