Accepted/Published papers

• [9]Jiangzhou Wang, Meier Wu, Yang Liu, Binghui Liu and Jianhua Guo. (2025). Joint community detection in random effects stochastic block models via the split-likelihood method, Journal of Computational and Graphical Statistics, 1–57.
• [8]Jiangzhou Wang, Binghui Liu, Jianhua Guo and Bing-yi Jing. (2025). Understanding asymptotic consistency and its unique advantages in large sample statistical inference, Journal of Multivariate Analysis, 1–17.
• [7]Peng Luo, Jiangzhou Wang, Yilong Wu and Wei Zhang. (2025). Inference of treatment benefit rate and treatment harm rate with missing endpoint and covariate. Statistics and Its Interface, 1–27. (alphabetical order).
• [6]Canhui Li, Jiangzhou Wang and Pengfei Wang. (2024). Large-scale dependent multiple testing via higher-order hidden Markov models. Journal of Biopharmaceutical Statistics, 1–13. (alphabetical order).
• [5]Jiangzhou Wang, Pengfei Wang. (2024). Large-scale dependent multiple testing via hidden semi-Markov models, Computational Statistics, 39, 1093–1126.
• [4]Jiangzhou Wang, Pengfei Wang, Tingting Cui and Wensheng Zhu. (2023). Covariate-modulated large-scale multiple testing under dependence, Computational Statistics and Data Analysis, 180, 107664.
• [3]Jiangzhou Wang, Jingfei Zhang, Binghui Liu, Ji Zhu and Jianhua Guo. (2023). Fast network community detection with profile-pseudo likelihood methods, Journal of the American Statistical Association, 118(542), 1359–1372.
• [2]Jiangzhou Wang, Binghui Liu and Jianhua Guo. (2021). Efficient split likelihood-based method for community detection of large-scale networks, Stat, 10(1), e349.
• [1]Jiangzhou Wang, Jianhua Guo and Binghui Liu. (2021). A fast algorithm for integrative community detection of multi-layer networks, Stat, 10(1), e348.

Submitted papers

• [1]Bing-yi Jing, Ting Li, Jiangzhou Wang and Ya Wang. Two-way node popularity model for directed and bipartite networks. Journal of Machine Learning Research. Under Revision, (alphabetical order).