## Research interest

• High-dimensional statistics

• Multiple testing

• Functional data analysis

• Time series and Econometrics

• Applications in genomics

## Some working papers

• Cao, H., Chen, J., and Zhang, X. (2020) Optimal False Discovery Rate Control for Large Scale Multiple Testing with Auxiliary Information. PDF GitHub

• Pramanik, S., and Zhang, X. (2020) Structure Adaptive Lasso. arXiv

• Chakraborty, S., and Zhang, X. (2019) A New Framework for Distance and Kernel-based Metrics in High-dimension. arXiv

• Zhang, X., and Bhattacharya, A. (2017) Empirical Bayes, SURE and Sparse Normal Mean Models. arXiv Latest version

• Zhang, X. (2017) Testing High Dimensional Mean Under Sparsity. PDF

## Selected forthcoming and published papers (more papers)

• Zhou, H., Zhang, X., and Chen, J. (2020) Covariate Adaptive Family-wise Error Rate Control for Genome-Wide Association Studies, Biometrika, forthcoming. arXiv GitHub

• Yi, S., and Zhang, X. (2020) Projection-based Inference for High-dimensional Linear Models, Statistica Sinica, forthcoming. PDF

• Zhang, X., and Chen, J. (2020) Covariate Adaptive False Discovery Rate Control with Applications to Omics-Wide Multiple Testing, Journal of the American Statistical Association, forthcoming. arXiv GitHub

• Yun, S., Zhang, X., and Li, B. (2020) Detection of Local Differences in Spatial Characteristics Between Two Spatiotemporal Random Fields, Journal of the American Statistical Association, forthcoming. Link

• Huang, J., Bai, L., Cui, B., Wu, L., Wang, L., An, Z., Ruan, S., Yu, Y., Zhang, X., and Chen, J. (2020) Leveraging Biological and Statistical Covariates Improves the Detection Power in Epigenome-wide Association Testing, Genome Biology, forthcoming. PDF

• Zhu, C., Zhang, X., Yao, S., and Shao, X. (2020) Distance-based and RKHS-based Dependence Metrics in High-dimension, The Annals of Statistics, forthcoming. PDF

• Lee, C., Zhang, X., and Shao, X. (2020) Testing the Conditional Mean Independence for Functional Data, Biometrika, forthcoming. PDF Supplement (R codes)

• Chakraborty, S., and Zhang, X. (2019) Distance Metrics for Measuring Joint Dependence with Application to Causal Inference, Journal of the American Statistical Association, 114, 1638-1650. arXiv Link (R package)

• Yao, S., Zhang, X., and Shao, X. (2018) Testing Mutual Independence in High Dimension via Distance Covariance, Journal of the Royal Statistical Society, Series B, 80, 455-480. arXiv Supplement (R codes)

• Zhang, X., Yao, S., and Shao, X. (2018) Conditional Mean and Quantile Dependence Testing in High Dimension, The Annals of Statistics, 46, 219-246. PDF Supplement

• Zhang, X., and Cheng, G. (2017) Simultaneous Inference for High-dimensional Linear Models, Journal of the American Statistical Association, 112, 757-768. PDF Supplement (R package)

• Zhang, X. (2016) White Noise Testing and Model Diagnostic Checking for Functional Time Series, Journal of Econometrics, 194, 76-95. PDF (R codes)

• Zhang, X. (2016) Fixed-smoothing Asymptotics in the Generalized Empirical Likelihood Estimation Framework, Journal of Econometrics, 193, 123-146. PDF

• Zhang, X., and Shao, X. (2016) On the Coverage Bound Problem of Empirical Likelihood Methods for Time Series, Journal of the Royal Statistical Society, Series B, 78, 395-421. PDF

• Zhang, X., and Shao, X. (2013) Fixed-smoothing Asymptotics for Time Series, The Annals of Statistics, 41, 1329-1349. PDF

• Shao, X., and Zhang, X. (2010) Testing for Change Points in Time Series, Journal of the American Statistical Association, 105, 1228-1240. PDF (R codes)