[1] Hanhan Li, Cong Li*. A study on the performance of matrix control charts based on the normal distribution, Journal of Quality Technology, 2026, 58(1): 57-83.（SCI）
[2] Xiaoxue Yang, Cong Li*, Dehui Wang. Modeling and monitoring of INARCH(p) process with geometrically inflated Poisson distribution, Quality and Reliability Engineering International, 2026, 42(3): 1189-1230.（SCI）
[3] Jianxuan Li, Cong Li*. Monitoring methods for process mean of a flexible bivariate integer-valued time series, Journal of Statistical Computation and Simulation, 2025, 95(13): 2745-2767.（SCI）
[4] Xuange Liu, Cong Li*. Monitoring procedures for binary integer autoregressive models with application to telephone complaint data, Statistics, 2025, 59(4): 950-969.（SCI）
[5] Nannan Li, Cong Li*, Jing Wan. Control charts for threshold correlated count data in disease infection number monitoring, Quality and Reliability Engineering International, 2024, 40(5): 2570-2583.（SCI）
[6] Hanhan Li, Cong Li*. Multivariate control charts for monitoring a bivariate correlated count process with application to meningococcal disease, Statistical Methods in Medical Research, 2023, 32(12): 2299-2317.（SCI）
[7] Cong Li, Haixiang Zhang*, Dehui Wang. Modelling and monitoring of INAR(1) process with geometrically inflated Poisson innovations. Journal of Applied Statistics, 2022, 49(7): 1821-1847.（SCI）
[8] Cong Li, Jianguo Sun*. Variable selection for high-dimensional quadratic Cox model with application to Alzheimer’s disease. The International Journal of Biostatistics, 2020, 16(2): 20190121.（SCI）
[9] Cong Li, Dehui Wang*, Fukang Zhu. Detecting mean increases in zero truncated INAR(1) processes. International Journal of Production Research, 2019, 57(17): 5589-5603.（SCI）
[10] Cong Li, Dehui Wang*, Jianguo Sun. Control charts based on dependent count data with deflation or inflation of zeros. Journal of Statistical Computation and Simulation, 2019, 89(17): 3273-3289.（SCI）
