Qian Xiao

Journal articles: 

1, Xiao, Q. and Xu, H.^* (2017), Construction of Maximin Distance Latin Squares and Related Latin Hypercube Designs, Biometrika, 104 (2), 455-464. 

2, Wang, L., Xiao, Q. and Xu, H.^* (2018), Optimal maximin $L_{1}$-distance Latin hypercube designs based on good lattice point designs, Annals of Statistics, 46 (6B), 3741-3766. (FastMmLHD in R package LHD)

3, Xiao, Q. and Xu, H.^* (2018), Construction of Maximin Distance Designs via Level Permutation and Expansion, Statistica Sinica, 28 (3), 1395-1414. 

4,  Xiao, Q., Wang, L. and Xu, H.^* (2019), Application of Kriging Models for a Drug Combination Experiment on Lung Cancer, Statistics in Medicine, 38 (2), 236-246.

5, Xiao, Q., Mandal, A., Lin, C. D., Deng, X.^* (2021), EzGP: Easy-to-interpret Gaussian Process models for computer experiments with both quantitative and qualitative factors, SIAM/ASA Journal on Uncertainty Quantification, 9.2, 333-353. (R Codes)

6, Xiao, Q.^* and Xu, H. (2021), A Mapping-based Universal Kriging Model for Order-of-addition Problems in Drug Combination Studies, Computational Statistics & Data Analysis, 157, 107-155. (Supplementary Material, R Codes)

7, Wang, Y., Peng Z., Zhang R., Xiao, Q.* (2021), Robust sequential design for piecewise-stationary multi-armed bandit problem in the presence of outliers, Statistical Theory and Related Fields, 5 (2), 122-133. (R Codes)

8, Cheng, W., Pan A., Rathbun S., Ge Y., Xiao, Q., Martinez L., Ling, F., Liu S., Wang X., Yu Z., Ebell M., Li C., Handel A., Chen E. and Ye, S^* (2021), Effectiveness of Neuraminidase Inhibitors to Prevent Mortality in Laboratory-Confirmed Avian Influenza A H7N9 Patients, International Journal of Infectious Diseases, 103, 573-578.

9, Chen, Z., Handel, A., Martinez, L., Xiao, Q., Li, C., Chen E., Pan, J., Li, Y., Ling, F., & Shen, Y.* (2021), The Impact of Social Distancing, Contact Tracing, and Case Isolation Interventions to Suppress the COVID-19 Epidemic: A Modeling Study, Epidemics, 36,100483.

10, Lukemire J., Xiao Q., Mandal A.*, Wong W. (2021), Statistical analysis of complex computer models in astronomy, The European Physical Journal Special Topics, 230:2253-2263. 

11, Wang, Y. Wang, F., Yuan, Y. Xiao, Q.* (2021), Connecting U-type designs before and after level permutations and expansions, Journal of Statistical Theory and Practice, 15, 81.

12, Li, C., Shen, Y.*, Xiao, Q., Rathbun, S., Huang, H., Guan, Y. (2022), Mean Corrected Generalized Estimating Equations for Longitudinal Binary Outcomes with Report Bias, Statistical Methods in Medical Research, 31(2):315-333.

13, Xiao, Q., Wang, Y., Mandal, A. & Deng, X*. (2022+), Modeling and active learning for experiments with quantitative-sequence factors, Journal of the American Statistical Association (published online), DOI: 10.1080/01621459.2022.2123335.

14, Xiao, Q., Joseph V. R*., Ray. D. M. (2022+), Maximum one-factor-at-a-time designs for screening in computer experiments, Technometrics (published online), DOI: 10.1080/00401706.2022.2141897; R-package MOFAT. 

15, Zhou, Y., Xiao, Q., Sun, F*. (2023), Construction of uniform projection designs via level permutation and expansion, Journal of Statistical Planning and Inference, 222: 209-225.

16, Li, Y., Pu, Y., Chang, C., Xiao, Q.* (2023+), A Scalable Gaussian Process for Large-Scale Periodic Data, Technometrics (published online), DOI: 10.1080/00401706.2023.2166124, Codes.

17, Li, Y., Zhang Y., , Xiao Q., and Wu, J.* (2023+), Quasi-Periodic Gaussian Process Modeling of Pseudo-Periodic Signals, IEEE Transactions on Signal Processing (Accept). 

(Corresponding author marked with *)

Book Chapters:

1, Jankar, J., Wang, H., Wilkes, L.R., Xiao, Q. & Mandal, A*. (2022), Design and Analysis of Complex Computer Models. In: Srinivas R., Kumar R., Dutta M. (eds) Advances in Computational Modeling and Simulation. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-16-7857-8_2.

Software development:

R package: LHD: Latin Hypercube designs.

R package LA: Lioness Algorithm.

R package MOFAT: Maximum One-Factor-at-a-Time Designs.