| Optimal detection of heterogeneous and heteroscedastic mixtures T Tony Cai, X Jessie Jeng, J Jin Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2011 | 156 | 2011 |
| Censored rank independence screening for high-dimensional survival data R Song, W Lu, S Ma, X Jessie Jeng Biometrika 101 (4), 799-814, 2014 | 133 | 2014 |
| Optimal sparse segment identification with application in copy number variation analysis XJ Jeng, TT Cai, H Li Journal of the American Statistical Association 105 (491), 1156-1166, 2010 | 92 | 2010 |
| Shrinkage and model selection with correlated variables via weighted fusion ZJ Daye, XJ Jeng Computational Statistics & Data Analysis 53 (4), 1284-1298, 2009 | 84 | 2009 |
| Simultaneous discovery of rare and common segment variants XJ Jeng, TT Cai, H Li Biometrika 100 (1), 157-172, 2013 | 60 | 2013 |
| Robust detection and identification of sparse segments in ultrahigh dimensional data analysis T Tony Cai, X Jessie Jeng, H Li Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2012 | 38 | 2012 |
| High-dimensional inference for personalized treatment decision XJ Jeng, W Lu, H Peng Electronic journal of statistics 12 (1), 2074, 2018 | 35 | 2018 |
| Rare variants association analysis in large-scale sequencing studies at the single locus level XJ Jeng, ZJ Daye, W Lu, JY Tzeng PLoS computational biology 12 (6), e1004993, 2016 | 21 | 2016 |
| Sparse covariance thresholding for high-dimensional variable selection XJ Jeng, ZJ Daye Statistica Sinica, 625-657, 2011 | 16 | 2011 |
| Efficient signal inclusion with genomic applications XJ Jeng, T Zhang, JY Tzeng Journal of the American Statistical Association, 2019 | 13 | 2019 |
| Some two-step procedures for variable selection in high-dimensional linear regression J Zhang, XJ Jeng, H Liu arXiv preprint arXiv:0810.1644, 2008 | 13 | 2008 |
| Parametric modeling of whole-genome sequencing data for CNV identification S Vardhanabhuti, XJ Jeng, Y Wu, H Li Biostatistics 15 (3), 427-441, 2014 | 8 | 2014 |
| Variable selection via adaptive false negative control in linear regression XJ Jeng, X Chen | 7 | 2019 |
| Estimating the proportion of signal variables under arbitrary covariance dependence XJ Jeng Electronic Journal of Statistics 17 (1), 950-979, 2023 | 5 | 2023 |
| Effective SNP ranking improves the performance of eQTL mapping XJ Jeng, J Rhyne, T Zhang, JY Tzeng Genetic epidemiology 44 (6), 611-619, 2020 | 5 | 2020 |
| Weak signal inclusion under dependence and applications in genome-wide association study XJ Jeng, Y Hu, Q Sun, Y Li The Annals of Applied Statistics 18 (1), 841-857, 2024 | 4 | 2024 |
| Predictor ranking and false discovery proportion control in high-dimensional regression XJ Jeng, X Chen Journal of Multivariate Analysis 171, 163-175, 2019 | 4 | 2019 |
| Detecting weak signals in high dimensions XJ Jeng Journal of Multivariate Analysis 147, 234-246, 2016 | 3 | 2016 |
| Transfer learning with false negative control improves polygenic risk prediction XJ Jeng, Y Hu, V Venkat, TP Lu, JY Tzeng PLoS genetics 19 (11), e1010597, 2023 | 2 | 2023 |
| Weak Signal Inclusion Under Sparsity and Dependence XJ Jeng, Y Hu arXiv preprint arXiv:2006.15667, 2020 | 1 | 2020 |
