Gao, Y., Pan, R.*, Li, F., Zhang, R. and Wang, H. (2024), “Grid point approximation for distributed nonparametric smoothing and prediction”, Journal of Computational and Graphical Statistics, accepted.
Zhang, Y., Pan, R.*, Zhu, X., Fang, K. * and Wang, H. (2024), “A latent space model for weighted keyword co-occurrence networks with applications in knowledge discovery in statistics”, Journal of Computational and Graphical Statistics, accepted.
Li, X., Gao, Y.*, Chang, H., Huang, D., Ma, Y., Pan, R., et al. (2024), “A selective review on statistical methods for massive data computation: distributed computing, subsampling, and minibatch techniques,” Statistical Theory and Related Fields, accepted.
Zhou, T., Pan, R.#, Zhang, J.*, and Wang, H. (2024), “An attribute-based Node2Vec model for dynamic community detection in co-authorship network,” Computational Statistics, accepted.
Pan, R., Liu, T., and Ma, L. (2024), “A Graph Attention Recurrent Neural Network Model for PM2.5 Prediction: A Case Study in China from 2015 to 2022”, Atmosphere, 15, 799.
Guo, B., Wang, L., Pan, R.*, and Zhu, X. (2024), “A grouped spatial-temporal model for PM2.5 data and its applications on outlier detection,” Communications in Statistics – Simulation and Computation, 53(5), 2565—2577.
Gao, T.,Pan, R.,Zhang, J.*, and Wang, H. (2024), “Community detection in temporal citation network via a tensor-based approach,” Statistics and Its Interface, 17(2), 145—158.
Gao, T., Liu, J.,Pan, R.*,and Wang, H. (2024), “Citation counts prediction of statistical publications based on multi-layer academic networks via neural network model,” Expert Systems with Applications, 238, 121634.
Ding,Y.,Pan, R.*, Zhang, Y., and Zhang, B. (2023), “A matrix completion bootstrap method for estimating scale-free network degree distribution,” Knowledge-Based Systems,277,110803.
Pan, R., Zhu, Y.*, Guo, B., Zhu, X., and Wang, H. (2023), “A sequential addressing subsampling method for massive data analysis under memory constraint,” IEEE Transactions on Knowledge and Data Engineering, 35(9), 9502-9513.
Zhang, Y.,Pan, R.*, Wang, H., and Su, H. (2023), “Community Detection in Attributed Collaboration Network for Statisticians,” Stat, 12(1), e507.
Pan, R., Ren, T.*, Guo, B., Li, F., Li, G., and Wang, H. (2022), “A note on distributed quantile regression by pilot sampling and one-step updating,” Journal of Business and Economics Statistics, 40(4), 1691—1700.
Zhu, X., Wu, S.*,Pan, R., and Wang, H. (2022), “Feature screening for massive data analysis by subsampling,” Journal of Business and Economics Statistics, 40(4), 1892—1903.
Song, X., Zhang, Y.*,Pan, R.*, and Wang, H. (2022), “Link prediction for statistical collaboration networks incorporating institutes and research interests,” IEEE Access, 10,104954—104965.
Pan, R., Chang, X.*, Zhu, X., and Wang, H. (2022), “Link prediction via latent space logistic regression model,” Statistics and Its Interface, 15(3), 267—282.
Gao, T., Zhang, Y., Wang, S., Yang, Y., and Pan, R.*(2021), “Community Detection for Statistical Citation Network by D-SCORE,” Statistics and Its Interface, 14(3), 279—294.
Zhu, X.,Pan, R.*, Zhang, Y., Chen, Y.,Mi, W.,and Wang, H. (2021), “Information Diffusion withNetworkStructures,”Statistics and Its Interface,14(2), 115—129.
Zhu, X.,Huang, D.*,Pan, R., and Wang, H. (2020), “Multivariate Spatial Autoregressive Modelfor Large Scale Social Networks,”Journal of Econometrics,215(2), 591—606.
Zhu, X., and Pan, R.*(2020),“Grouped Network Vector Autoregression,”Statistica Sinica,30(3), 1437—1462.
Ma, Y.,Pan, R.*, Zou, T., and Wang, H. (2020), “A Naive Least Squares Method for Spatial Autoregression with Covariates,” Statistica Sinica,30(2), 653—672.
Zhang, X.,Pan, R., Guan, G.*, Zhu, X., and Wang, H. (2020), “Logistic Regressionwith Network Structure,” Statistica Sinica,30(2), 673—693.
Zhou, J., Li, D.*,Pan, R., and Wang, H. (2020),“Network GARCH Model,”Statistica Sinica,30(3),1723—1740.
Cheng, H., Li, S., Ning, Y., Chen, X.,Pan, R., and Zhang, Z. (2020), “Analysis on utilization of Beijing local roads using taxi GPS data,” Physica A, 545, 123570.
Xu, K., Wang, J.*,Pan, R., and Wang, H. (2019),“Photographic Diary: A New Estimation Approach to PM2.5 Monitoring,”Statistics and Its Interface,12, 387—395.
Zhang, Y., Fan, J.,Pan, R.*, and Huang, L. (2019),“Usage Based Insurance with pointof interestdata,”Statistics and Its Interface, 12, 345—353.
Chen, Y.,Pan, R.*, Guan, R., and Wang, H. (2019),“A case study for Beijing Point of Interest Data Using Group Linked Cox Process,”Statistics and Its Interface, 12, 331—344.
Cai, W., Guan, G.,Pan, R.*, Zhu, X., and Wang, H. (2018), “Network Linear Discriminant Analysis,” Computational Statistics and Data Analysis, 117, 32—44.
Pan, R., Guan, R.*, Zhu, X., and Wang, H. (2018), “A Latent Moving Average Model for Network Regression,”Statistics and Its Interface, 11(4), 641—648.
Zhu, X.,Pan, R.*, Li, G., Liu, Y., and Wang, H. (2017), “Network Vector Autoregression,” Annals of Statistics, 45(3), 1096—1123.
Lan, W.,Pan, R., Luo, R.*, and Cheng Y. (2017),“High Dimensional Cross-Sectional Dependence Test under Arbitrary Serial Correlation,”Science China: Mathematics, 60, 345—360.
Pan, R., Wang, H.*, and Li, R. (2016),“Ultrahigh-Dimensional Multiclass Linear Discriminant Analysis by Pairwise Sure Independence Screening,”Journal of the American Statistical Association, 111(513), 169--179.
Zhu, X., Huang, D.*,Pan, R., and Wang, H. (2016),“An EM algorithm for click fraud detection,”Statistics and Its Interface, 9, 389-394.
Pan, R.*, and Wang, H. (2015),“A Note on Testing Conditional Independence for Social Network Analysis,”SCIENCE CHINA: Mathematics, 58(6), 1179-1190.
Pan,R., Wang, H.*, and Tsai, C. (2011),“Regression Analysis of Asymmetric Pairs in Large-Scale Network Data,”Communications in Statistics: Simulation and Computation, 40:10, 1540-1547.
Li, J.,Pan, R., and Wang, H. (2010),“Selection of Best Keywords: A Poisson Regression Model,”Journal of Interactive Advertising, 11(1), 27-35.
王菲菲,朱雪宁*,潘蕊(2021),广义网络向量自回归,中国科学:数学,51(8),1253--1266.
潘蕊,周静*,关蓉(2017),“网络中意见领袖对客户间接价值的影响,” 《商业研究》,59(9),28—32.