Wang, Zhonglei-School of Economics, Xiamen University

People

People

Wang, Zhonglei

Associate Professor
Phone:
Email:wangzl at xmu dot edu dot cn
Office:A122
Office Hours:R 12:30--2:30 pm
Homepage:

Profile Research results Research projects

Working experience

2022.8-present, Associate Professor, Wang Yanan Institute for Studies in Economics (WISE) and Department of Statistics, School of Economics, Xiamen University

2018.8-2022.8, Assistant Professor, Wang Yanan Institute for Studies in Economics (WISE) and Department of Statistics, School of Economics, Xiamen University

Education

Ph.D., Statistics, Iowa State University, 2018

M.S., Education, Beijing Normal University, 2012

B.S., Mathematics and Applied Mathematics, Beijing Normal University, 2010

Research interests

Survey Sampling.

Courses:

Neural Network and Deep Learning: 2022F

Ordinary Differential Equation: 2022S, 2021S, 2020S, 2019S

Survey Sampling (Master): 2021F, 2020F, 2019F

Probability: 2018F

  1. He, X., Mao, X., and Wang, Z. (2023), Nonparametric augmented probability weighting with sparsity, Computational Statistics & Data Analysis, (To appear soon).

  2. Kim, J.K., Rao, J.N.K., and Wang, Z. (2023), Hypotheses Testing from Complex Survey Data Using Bootstrap Weights: A Unified Approach, Journal of the American Statistical Association, (To appear soon).

  3. Wang, Z, Kim, H.J. and Kim, J.K. (2022), Survey data integration for regression analysis using model calibration, Survey Methodology, (To appear soon).

  4. Wang, Z and Kim, J.K. (2022), Comments on "Statistical inference with non-probability survey samples", Survey Methodology, 48(2), 361-366.

  5. Mao, X., Wang, Z and Yang, S. (2022), Matrix completion under complex survey sampling, Annals of the Institute of Statistical Mathematics, (To appear soon).

  6. Wang, Z, Peng, L., and Kim, J.K. (2022), Bootstrap Inference for the Finite Population Mean under Complex Sampling Designs, Journal of the Royal Statistical Society Series B (Statistical Methodology), 84(4), 1150-1174.

  7. Mao, X., Peng, L., and Wang, Z. (2022), Nonparametric Feature Selection by Random Forests and Deep Neural Networks, Computational Statistics & Data Analysis, (To appear soon).

  8. Zhang, X., Wang, Y.P., Rayner, P.J. et al. (2021), A small climate-amplifying effect of climate-carbon cycle feedback, Nature Communications, 12, 2952.

  9. Wang, Z. (2019), Monte Carlo Sampling Using Reservoir, Computational Statistics & Data Analysis, 139, 64-74.

  10. Wang, Z. and Zhu, Z. (2019). Spatiotemporal Balanced Sampling Design for Longitudinal Area Survey, Journal of Agriculture, Biological and Environmental Statistics, 24(2), 245-263.

  11. Kim, J.K. and Wang, Z. (2018). Some Sampling Techniques for Big Data Analysis, International Statistics Review, 84(S1), S177-S191.

  12. Wang, Z., Kim J. K. and Yang, S. (2018). Approximate Bayesian Inference under Informative Sampling, Biometrika, 105(1), 91-102.

  13. Yin, S., Wang, Z., Zhu, Z., Zou, X. and Wang, W. (2018). Using Kriging with a Heterogeneous Measurement Error to Improve the Accuracy of Extreme Precipitation Return Level Estimation, Journal of Hydrology, 562, 518-529.

  14. Kim, J.K., Wang, Z., Zhu, Z.and Cruze, N.(2018). Combining survey and non-survey data for improved sub-area prediction using a multi-level model, Journal of Agriculture, Biological and Environmental Statistics, 23(2), 175-189.

  15. Huang, C., Zheng, X., Tail, A. et al. (2014), On using smoothing spline and residual correction to fuse rain gauge observations and remote sensing data, Journal of Hydrology, 508(16), 410-417

  16. Li, T., Zheng, X., Dai, Y. et al. (2014), Mapping near-surface air temperature, pressure, relative humidity and wind speed over Mainland China with high spatiotemporal resolution, Advances in Atmospheric Sciences, 31(5), 1127-1135

  17. Conference:

  18. Pu, Y., Feng, Z., Wang, Z., Yang, Z. and Li, J. (2021). Anomaly Detection for In situ Marine Plankton Images, ICCV Workshop in Computer Vision in the Ocean.

  19. Wang, H., Zhang, Y., Mao, X., and Wang, Z. (2023) Transductive Matrix Completion with Calibration for Multi-Task Learning, ICASSP (CCF B), (To appear soon).

  • NSFC Key Program (7203002), Research on the theory, method and application of economic big data, 2021/01--2025/12, Member.

  • NSFC for Young Scholars (11901487), The statistical inference by bootstrap under complex sampling design, 2020/01--2022/12, PI.

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