Selected Preprints (google scholar)

• Z. Zhao, F. Jiang, Y. Yu, X. Chen 

High-dimensional dynamic pricing under non-stationarity: learning and earning with change-point detection, under major revision at MS. - paper

• C. Ke, R. Wang, Z.Zhao

Discrete choice models with piecewise linear utility: modeling, estimation and pricing, under major revision at MSOM. - paper

• R. Wang, Z. Zhao, C. Ke

Modeling consumer choice and optimizing assortment under the threshold multinomial logit model, R&R at MS. - paper

• D. Wang, Z. Zhao

Optimal change-point testing for high-dimensional linear models with temporal dependence, in submission. - paper

• S. Sun, Z. Zhao, F. Jiang, X. Shao

SNSeg: An R package for time series segmentation via self-normalization, in submission. - paper

• Z. Zhao, L. Chen, L. Lin

Change-point detection in dynamic networks via graphon estimation. - paper

Publications

• H. Xu, D. Wang, Z. Zhao, Y. Yu (2024+) 

Change point inference in high-dimensional regression models under temporal dependence. - paper

Annals of Statistics. (Accepted)

• Z. Zhao, T.F. Ma, W.L. Ng, C.Y. Yau (2024+)

A composite likelihood-based approach for change-point detection in spatiotemporal processes. - paper

Journal of the American Statistical Association. (Accepted)

• P. Shi, Z. Zhao (2024+)

Enhanced pricing and management of bundled insurance risks with dependence-aware prediction using pair copula construction. - paper

Journal of Econometrics. (Accepted)

• R. Wang, C. Ke, Z. Zhao (2024+)

Anticipated wait and its effects on consumer choice, pricing, and assortment management. - paper

Manufacturing and Service Operations Management. (Accepted)

• F. Jiang, Z. Zhao, X. Shao (2023)

Time series analysis of COVID-19 infection curve: a change-point perspective. - paper

Journal of Econometrics.

• C. Padilla, D. Wang, Z. Zhao, Y. Yu (2022)

Change-point detection for sparse and dense functional data in general dimensions. - paper

Neural Information Processing Systems.

• Z. Zhao, F. Jiang, X. Shao (2022)

Segmenting time series via self-normalization. - paper, package

Journal of the Royal Statistical Society - Series B. 

• D. Wang, Z. Zhao, Y. Yu, R. Willett (2022)

Functional linear regression with mixed predictors. - paper

Journal of Machine Learning Research.

• D. Wang, Z. Zhao, K. Lin, R. Willett (2021)

Statistically and computationally efficient change point localization in regression settings. - paper

Journal of Machine Learning Research. 

• F. Jiang, Z. Zhao, X. Shao (2021)

Modelling the COVID-19 infection trajectory: A piecewise linear quantile trend model. - paper

Journal of the Royal Statistical Society - Series B, with discussion.

• Y. He, L. Peng, D. Zhang, Z. Zhao (2021)

Risk analysis via generalized Pareto distributions. - paper

Journal of Business & Economic Statistics.

• Z. Zhao, C.Y. Yau (2021)

Alternating dynamic programming for multiple epidemic change-point estimation. - paper

Journal of Computational and Graphical Statistics.

• Z. Zhao, P. Shi, Z. Zhang (2021)

Modeling multivariate time series with copula-linked univariate D-vines. - paper

Journal of Business & Economic Statistics.

• Z. Zhao, P. Shi, X. Feng (2020)

Knowledge learning of insurance risks using dependence models. - paper

INFORMS Journal on Computing.

• Z. Zhao (2020)

Dynamic bivariate peak over threshold model for joint tail risk dynamics of financial markets. - paper

Journal of Business & Economic Statistics.

• P. Shi, Z. Zhao (2020)

Regression for copula-linked compound distributions with applications in modeling aggregate insurance claims. - paper

Annals of Applied Statistics.

• Z. Zhao, Z. Zhang (2018)

Semi-parametric dynamic max-copula model for multivariate time series. - paper

Journal of the Royal Statistical Society - Series B.

• Z. Zhao, Z. Zhang, R. Chen (2018)

Modeling maxima with autoregressive conditional Frechet model. - paper

Journal of Econometrics.

• C.Y. Yau, Z. Zhao (2016)

Inference for multiple change-points in time series via likelihood ratio scan statistics. - paper

Journal of the Royal Statistical Society - Series B.

• K. West, Z. Zhao (2016)

Regressor and disturbance have moments of all order, least squares estimator has none. - paper

Statistics & Probability Letters.

Fundings

• NSF DMS-2014053 (PI)

• Oracle Labs (PI)

Referee services

• Journal of Econometrics, Journal of Business & Economic Statistics, Annals of Statistics, Journal of Royal Statistical Society - Series B, Journal of American Statistical Association, Biometrika, Scandinavian Journal of Statistics, TEST, Canadian Journal of Statistics, Statistica Sinica, Stat, SIAM Review, Statistics and Computing, Computational Statistics & Data Analysis, Journal of Money, Credit and Banking, Extremes, Journal of Royal Statistical Society - Series A, INFORMS - Journal on Computing, MISQ, ISR, POM, Management Science, Electronic Journal of Statistics