Research

REFEREED PAPERS

(* indicates alphabetical ordering authorship; # indicates corresponding authorship; underlined authors are students under my supervision.)

1. Sun, Y., Ma, L. and Xia, Y.# (2024+), A Decorrelating and Debiasing Approach to Simultaneous Inference for High-Dimensional Confounded Models, Journal of the American Statistical Association, to appear.

2. Ma, L., Xia, Y.# and Li, L. (2024+), NAPA: Neighborhood-Assisted and Posterior-Adjusted Two-sample Inference.  Statistica Sinica, to appear.

3. Wang, X., Liu, M., Nogues, I.E., Chen, T., Xiong, X., Bonzel, C.L., Zhang, H., Hong, C., Xia, Y., Dahal, K., Costa, L., Cui, J., VA Million Veteran Program, Gaziano, J.M., Kim, SC., Ho, Y.L., Cho, K., Cai, T. and Liao, KP. (2024), Heterogeneous associations between interleukin-6 receptor variants and phenotypes across ancestries and implications for therapy. Scientific Reports 14, 1-12.

4. Xia, Y.# and Cai, T.T. (2023), Discussion of “A Scale-free Approach for False Discovery Rate Control in Generalized Linear Models”, Journal of the American Statistical Association, 118(543), 1569-1572.

5. *Cai, T.T., Guo, Z. and Xia, Y.# (2023), Statistical Inference and Large-scale Multiple Testing for High-dimensional Regression Models (with discussion), Test, 32, 1135-1171.  

6. *Cai, T.T., Guo, Z. and Xia, Y.# (2023), Rejoinder on: Statistical Inference and Large-scale Multiple Testing for High-dimensional Regression Models, Test, 32, 1187-1194.

7. *Chen, H. and Xia, Y.# (2023), A Normality Test for High-dimensional Data based on the Nearest Neighbor Approach. Journal of the American Statistical Association, 118(541), 719-731.

8. Chen, X., Yang, D.#, Xu, Y., Xia, Y.#, Wang, D. and Shen, H. (2023), Testing and Support Recovery of Correlation Structures for Matrix-Valued Observations with an Application to Stock Market Data. Journal of Econometrics, 232(2), 544-564.

9. *Cai, Tianxi, Liu, M. and Xia, Y.# (2022), Individual Data Protected Integrative Regression Analysis of High-dimensional Heterogeneous Data. Journal of the American Statistical Association, 117(540), 2105-2119.

10. *Cai, T.T., Sun, W. and Xia, Y.# (2022), LAWS: A  Locally Adaptive Weighting and Screening Approach To Spatial Multiple Testing. Journal of the American Statistical Association, 117(539), 1370-1383.

11. Xia, Y. and Li, L. (2022), Hypothesis Testing for Network Data with Power Enhancement. Statistica Sinica, 32, 293-321.

12. Liu, M., Xia, Y.#, Cho, K, and Cai, Tianxi (2021), Integrative High-dimensional Multiple Testing with Heterogeneity under Data Sharing Constraints. Journal of Machine Learning Research, 22, 1-26.

13. Xia, Y., Li, L., Lockhart, S. and Jagust, W. (2020), Simultaneous Covariance Inference for Multimodal Integrative Analysis. Journal of the American Statistical Association, 115, 1279-1291.

14. Xia, Y., Cai, T.T. and Sun, W. (2020), GAP: A General Framework for Information Pooling in Two-Sample Sparse Inference. Journal of the American Statistical Association, 115, 1236-1250.

15. Ye, Y., Xia, Y. and Li, L. (2021), Paired Test of Matrix Graphs and Brain Connectivity Analysis. Biostatistics, 22, 402-420.

16. *Cai, T. T., Li, H., Ma, J. and Xia, Y. (2019), Differential Markov Random Field Analysis with an Application to Detecting Differential Microbial Community Networks. Biometrika, 106, 401-416.

17. Xia, Y. and Li, L. (2019), Matrix Graph Hypothesis Testing and Application in Brain Connectivity Alternation Detection. Statistica Sinica, 29, 303-328.

18. Xia, Y., Cai, T. T., and Li, H. (2018), Joint Testing and False Discovery Rate Control in High-Dimensional Multivariate Regression. Biometrika, 105(2), 249-269.

19. Xia, Y., Cai, T. and Cai, T.T. (2018), Multiple Testing of Submatrices of a Precision Matrix with Applications to Identification of Between Pathway Interactions. Journal of the American Statistical Association, 113(521), 328-339.

20. Xia, Y., Cai, T. and Cai, T.T. (2018), Two-Sample Tests for High-Dimensional Linear Regression with an Application to Detecting Interactions. Statistica Sinica, 28, 63-92.

21. Xia, Y. (2017), Testing and Support Recovery of Multiple High-Dimensional Covariance Matrices with False Discovery Rate Control. Test, 26(4), 782-801.

22. Xia, Y. and Li, L. (2017), Hypothesis Testing of Matrix Graph Model with Application to Brain Connectivity Analysis. Biometrics, 73(3), 780-791.

23. Xia, Y., Cai, T. and Cai, T.T. (2015), Testing Differential Networks with Applications to the Detection of Gene-Gene Interactions. Biometrika, 102, 247-266.

24. *Cai, T.T., Liu, W. and Xia, Y. (2014), Two-Sample Test of High Dimensional Means Under Dependence. Journal of the Royal Statistical Society, Series B, 76, 349-372.

25. *Cai, T.T. and Xia, Y.# (2014), High-Dimensional Sparse MANOVA. Journal of Multivariate Analysis, 131, 174-196.

26. *Cai, T.T., Low, M. and Xia, Y. (2013), Adaptive Confidence Intervals for Regression Functions Under Shape Constraints. The Annals of Statistics, 41, 722-750.

27. *Cai, T.T., Liu, W. and Xia, Y. (2013), Two-Sample Covariance Matrix Testing and Support Recovery in High-Dimensional and Sparse Settings. Journal of the American Statistical Association, 108, 265-277.

TECHNICAL REPORTS

1. Liang, Z., Cai, T.T., Sun, W. and Xia, Y.# (2023), Locally Adaptive Algorithms for Multiple Testing with Network Structure, with Application to Genome-Wide Association Studies. Technical Report.

2. Ma, L., Qin, S. and Xia, Y.# (2023), Alteration Detection of Tensor Dependence Structure via Sparsity-Exploited Reranking Algorithm. Technical Report.

3. Gang, B., Qin, S. and Xia, Y.# (2023), A Unified and Optimal Ranking and Thresholding Framework for Multiple Testing. Technical Report.

4. Zhou, X., Xia, Y.# and Li, L. (2023), Estimation and Inference for High-dimensional Multi-response Growth Curve Model. Technical Report.