Refereed Publications
Tang, X., and Zhang, L. (2024) A Hierarchical Gamma Prior for Modeling Random Effects in Small Area Estimation. Survey Methodology. Accepted.
Zhang, S., Tang, X., He, Q., Liu, J., and Ying, Z. (2024) External Correlates of Adult Digital Problem-Solving Process: An Empirical Analysis of PIAAC PSTRE Action Sequences. Zeitschrift fur Psuchologie. 232(2), 120-136. link
Tang, X. (2024) A Latent Hidden Markov Model for Process Data. Psychometrika. 89, 205-240. link
Tang, X., and Ghosh, M. (2023) Global-Local Priors for Spatial Small Area Estimation. Calcutta Statistical Association Bulletin. 75(2), 141-154. link
Wang, Z., Tang, X., Liu, J., and Ying, Z. (2022) Subtask Analysis of Process Data Through a Predictive Model. British Journal of Mathematical and Statistical Psychology. 76(1), 211-235. link
Lippitt, W. Sethuraman, S., and Tang, X. (2022) Stationarity and Inference in Multistate Promoter Models of Stochastic Gene Expression via Stick-Breaking Measures. SIAM Journal on Applied Mathematics. 82(6), 1953-1986. link
Ghosh, T., Ghosh, M., Maples, J., and Tang, X. (2022) Multivariate Global-Local Priors for Small Area Estimation. Stats. 5(3), 673-688. link
Tang, X., Wang, Z., Zhang, S., Liu, J., and Ying, Z. (2021) ProcData: An R Package for Process Data Analysis. Psychometrika. 86, 1058-1083. link
Tang, X., Wang, Z., Liu, J., and Ying, Z. (2021) An Exploration of Process Data by Action Sequence Autoencoder. British Journal of Mathematical and Statistical Psychology. 74, 1-33. link
Wang, Z., Tang, X., and Liu, J. (2020) Statistical Analysis of Multi-Relational Network Recovery. Frontiers in Applied Mathematics and Statistics. link
Tang, X., Wang, Z., He, Q., Liu, J., and Ying, Z. (2020) Latent Feature Extraction for Process Data Using Multidimensional Scaling. Psychometrika. 85, 378-397. link
Merrill, H. R., Tang, X., and Bliznyuk, N. (2019) Spatio-Temporal Additive Regression Models Selection for Urban Water Demand. Stochastic Environmental Research and Risk Assessment. 33(4), 1075-1087. link
Tang, X., Yang, Y., Yu, H., Liao, Q., and Bliznyuk, N.(2019) A Spatio-Temporal Modeling Framework for Surveillance Data of Multiple Infectious Pathogens with Small Laboratory Validation Sets. Journal of American Statistical Association. Accepted. link
Tang, X., Chen, Y., Li, X., Liu, J., and Ying, Z. (2019) A Reinforcement Learning Approach to Personalized Learning Recommendation System. British Journal of Mathematical and Statistical Psychology 72, 108-135. link
Tang, X., Ghosh, M., Ha, N. S., and Sedransk, J. (2018) Modeling Random Effects Using Global-Local Shrinkage Priors in Small Area Estimation. Journal of American Statistical Association 113, 1476-1489. link
Tang, X., Xu, X., Ghosh, M., and Ghosh, P. (2018) Bayesian Variable Selection and Estimation Based on Global-local Shrinkage Priors. Sankhya A 80(2), 215-246. link
Tang, X., Li, K., Ghosh, M. (2017). Bayesian Multiple Testing Under Sparsity for Polynomial-Tailed Distributions. Statistica Sinica 27, 1225-1242. link
Ghosh, P., Tang, X., Ghosh, M., and Chakrabarti, A. (2016). Asymptotic Properties of Bayes Risk for a General Class of Shrinkage Priors in Multiple Hypothesis Testing under Sparsity. Bayesian Analysis 11(3), 753-796. link
Submitted Manuscripts
Zhu, Z., Tang, X. Bayesian Shrinkage with Log-Cauchy Priors. Under Major Revision.
Tang, X., and Fuquene-Patino, J. Shrinkage Priors for Functional and Structural Small Area Estimation with Applications to Family Planning Indicators. Under Major Revision.
Tang, X., Liu, J., and Ying, Z. Response Process Signature. Submitted.
Working Papers
Zhu, Z., Tang, X., and Zhou, S. Bayesian Region Selection with Spatially Dependent Global-Local Shrinkage Priors.
Tang, X., and Zhang, S. Hidden Markov Cognitive Diagnostic Models for Response Process Data.
Yin, Z., Liu, C., Zhang, L., and Tang, X. Differential Omics Analysis Based on the Zero-Inflated Negative Binomial Distribution.