| Inference for multiple change points in time series via likelihood ratio scan statistics CY Yau, Z Zhao Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2016 | 83 | 2016 |
| Time series analysis of COVID-19 infection curve: A change-point perspective F Jiang, Z Zhao, X Shao Journal of Econometrics, 2023 | 70 | 2023 |
| Statistically and computationally efficient change point localization in regression settings D Wang, Z Zhao, KZ Lin, R Willett Journal of Machine Learning Research 22 (248), 1-46, 2021 | 39 | 2021 |
| Change-point detection in dynamic networks via graphon estimation Z Zhao, L Chen, L Lin arXiv preprint arXiv:1908.01823, 2019 | 36 | 2019 |
| Modeling maxima with autoregressive conditional Fréchet model Z Zhao, Z Zhang, R Chen Journal of Econometrics 207 (2), 325-351, 2018 | 27 | 2018 |
| Modelling the COVID-19 infection trajectory: A piecewise linear quantile trend model F Jiang, Z Zhao, X Shao Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2022 | 23 | 2022 |
| Regression for copula-linked compound distributions with applications in modeling aggregate insurance claims P Shi, Z Zhao Annals of Applied Statistics 14 (1), 357-380, 2020 | 21 | 2020 |
| Change point inference in high-dimensional regression models under temporal dependence H Xu, D Wang, Z Zhao, Y Yu Annals of Statistics, 2024 | 18 | 2024 |
| Dynamic bivariate peak over threshold model for joint tail risk dynamics of financial markets Z Zhao Journal of Business & Economic Statistics 39 (4), 892-906, 2021 | 17 | 2021 |
| Modeling multivariate time series with copula-linked univariate d-vines Z Zhao, P Shi, Z Zhang Journal of Business & Economic Statistics 40 (2), 690-704, 2022 | 16 | 2022 |
| Semiparametric dynamic max-copula model for multivariate time series Z Zhao, Z Zhang Journal of the Royal Statistical Society Series B 80 (2), 409-432, 2018 | 16 | 2018 |
| Copula-based joint modeling of crash count and conflict risk measures with accommodation of mixed count-continuous margins D Yang, K Xie, K Ozbay, Z Zhao, H Yang Analytic Methods in Accident Research 31, 100162, 2021 | 14 | 2021 |
| Segmenting time series via self-normalisation Z Zhao, F Jiang, X Shao Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2022 | 13 | 2022 |
| Optimal change-point testing for high-dimensional linear models with temporal dependence D Wang, Z Zhao arXiv preprint arXiv:2205.03880, 2022 | 11 | 2022 |
| Risk analysis via generalized Pareto distributions Y He, L Peng, D Zhang, Z Zhao Journal of Business & Economic Statistics 40 (2), 852-867, 2022 | 10 | 2022 |
| Functional linear regression with mixed predictors D Wang, Z Zhao, Y Yu, R Willett Journal of Machine Learning Research 23 (266), 1-94, 2022 | 9 | 2022 |
| Knowledge learning of insurance risks using dependence models Z Zhao, P Shi, X Feng INFORMS Journal on Computing 33 (3), 1177-1196, 2021 | 9 | 2021 |
| A Composite Likelihood-based Approach for Change-point Detection in Spatio-temporal Processes Z Zhao, TF Ma, WL Ng, CY Yau Journal of the American Statistical Association, 2024 | 8 | 2024 |
| Enhanced Pricing and Management of Bundled Insurance Risks with Dependence-aware Prediction using Pair Copula Construction P Shi, Z Zhao Journal of Econometrics, 2024 | 6* | 2024 |
| Alternating pruned dynamic programming for multiple epidemic change-point estimation Z Zhao, CY Yau Journal of Computational and Graphical Statistics 30 (3), 808-821, 2021 | 5 | 2021 |
Daren WangUniversity of Notre DameVerified email at nd.edu
