| Specifying prior distributions in reliability applications Q Tian, C Lewis‐Beck, JB Niemi, WQ Meeker Applied Stochastic Models in Business and Industry, 2023 | 16 | 2023 |
| Methods to compute prediction intervals: A review and new results Q Tian, DJ Nordman, WQ Meeker Statistical Science 37 (4), 580-597, 2022 | 15 | 2022 |
| Prediction of Future Failures for Heterogeneous Reliability Field Data C Lewis-Beck, Q Tian, WQ Meeker Technometrics 64 (1), 2021 | 10 | 2021 |
| Predicting the number of future events Q Tian, F Meng, DJ Nordman, WQ Meeker Journal of the American Statistical Association 117 (539), 1296-1310, 2022 | 8 | 2022 |
| Using degradation models to assess pipeline life Q Tian, S Liu, WQ Meeker Applied Stochastic Models in Business and Industry 35 (6), 1411-1430, 2019 | 6 | 2019 |
| ELSA: Efficient Label Shift Adaptation through the Lens of Semiparametric Models Q Tian, X Zhang, J Zhao International Conference on Machine Learning, 2023 | 4 | 2023 |
| Constructing Prediction Intervals Using the Likelihood Ratio Statistic Q Tian, DJ Nordman, WQ Meeker INFORMS Journal on Data Science 1 (1), 63-80, 2022 | 2 | 2022 |
| Efficient and Model-Agnostic Parameter Estimation Under Privacy-Preserving Post-randomization Data Q Tian, J Zhao arXiv preprint arXiv:2403.07288, 2024 | | 2024 |
| ReTaSA: A Nonparametric Functional Estimation Approach for Addressing Continuous Target Shift H Kim, X Zhang, J Zhao, Q Tian International Conference on Learning Representations, 2024 | | 2024 |
| Rejoinder to “Specifying Prior Distribution in Reliability Applications” Q Tian, C Lewis‐Beck, JB Niemi, WQ Meeker Applied Stochastic Models in Business and Industry, 2023 | | 2023 |
| Prediction interval methods for reliability data Q Tian Iowa State University, 2021 | | 2021 |
William Q. MeekerDistinguished Professor of Statistics at Iowa State UniversityVerified email at iastate.edu
