[14]  Maolin Yang, Muyi Li* and Guodong Li (2024). On Memory-Augmented Gated Recurrent Unit Network, International Journal of Forecasting, Accepted.

[13] Xuqin Wang and Muyi Li* (2023).  Bootstrapping the transformed goodness-of-fit test on heavy-tailed GARCH models, Computational Statistics & Data  Analysis,  Vol(184),107744.

[12]  Muyi Li* and Yanfen Zhang (2022),  Bootstrapping Multivariate Portmanteau Tests for vector autoregressive models with weak assumptions on errors, Computational Statistics & Data  Analysis,  Vol(65),107321.

[9] Dong Li, Muyi Li* and Lianbin Zeng (2019). Simulation and application of subsampling for threshold autoregressive moving-average models. Communications in Statistics Simulation and Computation,  Vol 51(5), 2110-2121.

[8] Yan Han, Ying Yuan, Sha Cao,  Muyi Li and  Yong Zang. (2019). On the Use of Marker Strategy Design to Detect Predictive Marker Effect in Cancer Immunotherapy and Targeted Therapy. Statistics in Biosciences, 1-16.  

[7] Shaojun Guo, Dong Li and Muyi Li* (2019). Strictly Stationarity Testing and GLAD estimation of Double AR Models. Journal of Econometrics, Vol 221(2), 319-337.

[6] C.W.S. Chen, Muyi Li, N.T.H.Nguyen and S.Sriboonchita (2017). On Asymmetric Market Model with Heteroscedasticity and Quantile Regression. Computational Economics, Vol 49:155-174.  

[5] Muyi Li, Guodong Li and Wai Keung Li (2015). On a New Hyperbolic GARCH Model.Journal of Econometrics, Vol 189(2), 428-436.  

[4] Dong Li, Muyi Li*, Wuqing Wu (2014). On Dynamics of Volatilities in Nonstationary GARCH Model.  Statistics and Probability Letters. Vol 94, 86-90.  

[3] Muyi Li and Yongxiang Huang (2014).  Hilbert-Huang Transform based Multifractal  Analysis of China Stock Market.  Physica A: Statistical Mechanics and its Applications, 406, 222-229.    

[2] Muyi Li*, Wai Keung Li and Guodong Li (2013). On Mixture Memory GARCHModels. Journal of Time Series Analysis, 34: 606-624. (Lead article in this issue)  

[1] Muyi Li , Guodong Li and Wai Keung Li (2011). Score Tests for Hyperbolic GARCH  Models.   Journal of Business and Economic Statistics , Vol 29(4):579-586.

中文发表：

[4] 李木易, 童晨, 张晓林.基于LAD-LASSO的多门限波动率模型估计与应用。2023, 数理统计与管理，Vol(43), 559-570.

[3] 闫语、方亚、李木易、曾雁冰。隔代照料对老年人社会参与的影响——基于2018年CHARLS数据的实证研究。中国卫生事业管理，2022，39（09）：699-703。

[2] 李木易、方颖。动态混合HGARCH模型的估计和预测。管理科学学报，2020， Vol(5), 1-12。  

[1] 李木易。《时间序列分析》的理论基础与数据实践——浅谈本科实验教学和教学改革。经济资料译丛，2020, Vol 183, 61-66.