Xinge Jeng

Jeng, X. J., Hu, Y., Sun, Q., & Li, Y. (2024). WEAK SIGNAL INCLUSION UNDER DEPENDENCE AND APPLICATIONS IN GENOME-WIDE ASSOCIATION STUDY. ANNALS OF APPLIED STATISTICS, 18(1), 841–857. https://doi.org/10.1214/23-AOAS1815

Jeng, X. J. (2023). Estimating the proportion of signal variables under arbitrary covariance dependence. ELECTRONIC JOURNAL OF STATISTICS, 17(1), 950–979. https://doi.org/10.1214/23-EJS2119

Jeng, X. J., Hu, Y., Venkat, V., Lu, T.-P., & Tzeng, J.-Y. (2023). Transfer learning with false negative control improves polygenic risk prediction. PLOS GENETICS, 19(11). https://doi.org/10.1371/journal.pgen.1010597

Jeng, X. J., Peng, H., & Lu, W. (2021). Model Selection With Mixed Variables on the Lasso Path. SANKHYA-SERIES B-APPLIED AND INTERDISCIPLINARY STATISTICS, 83(1), 170–184. https://doi.org/10.1007/s13571-019-00219-5

Jeng, X. J., Rhyne, J., Zhang, T., & Tzeng, J.-Y. (2020). Effective SNP ranking improves the performance of eQTL mapping. GENETIC EPIDEMIOLOGY, 44(6), 611–619. https://doi.org/10.1002/gepi.22293

Rhyne, J., Jeng, X. J., Chi, E. C., & Tzeng, J.-Y. (2020). FastLORS: Joint modelling for expression quantitative trait loci mapping in R. STAT, 9(1). https://doi.org/10.1002/sta4.265

Jeng, X. J., & Chen, X. (2019). Predictor ranking and false discovery proportion control in high-dimensional regression. JOURNAL OF MULTIVARIATE ANALYSIS, 171, 163–175. https://doi.org/10.1016/j.jmva.2018.12.006

Jeng, X. J., & Chen, X. (2019). Variable selection via adaptive false negative control in linear regression. ELECTRONIC JOURNAL OF STATISTICS, 13(2), 5306–5333. https://doi.org/10.1214/19-EJS1649

Jeng, X. J., Zhang, T., & Tzeng, J.-Y. (2018). Efficient Signal Inclusion With Genomic Applications. Journal of the American Statistical Association, 1–23. https://doi.org/10.1080/01621459.2018.1518236

Jeng, X. J., Lu, W., & Peng, H. (2018). High-dimensional inference for personalized treatment decision. ELECTRONIC JOURNAL OF STATISTICS, 12(1), 2074–2089. https://doi.org/10.1214/18-ejs1439

Jeng, X. J. (2016). Detecting weak signals in high dimensions. JOURNAL OF MULTIVARIATE ANALYSIS, 147, 234–246. https://doi.org/10.1016/j.jmva.2016.02.004

Jeng, X. J., Daye, Z. J., Lu, W. B., & Tzeng, J. Y. (2016). Rare variants association analysis in large-scale sequencing studies at the single locus level. PLoS Computational Biology, 12(6).

Song, R., Lu, W., Ma, S., & Jeng, X. (J. (2014). Censored rank independence screening for high-dimensional survival data. Biometrika, 101(4), 799–814. https://doi.org/10.1093/biomet/asu047

Vardhanabhuti, S., Jeng, X. J., Wu, Y., & Li, H. (2014). Parametric modeling of whole-genome sequencing data for CNV identification. BIOSTATISTICS, 15(3), 427–441. https://doi.org/10.1093/biostatistics/kxt060

Jeng, X. J., Cai, T. T., & Li, H. (2013). Simultaneous discovery of rare and common segment variants. BIOMETRIKA, 100(1), 157–172. https://doi.org/10.1093/biomet/ass059

Daye, Z. J., & Jeng, X. J. (2009). Shrinkage and model selection with correlated variables via weighted fusion. Computational Statistics & Data Analysis, 53(4), 1284–1298. https://doi.org/10.1016/j.csda.2008.11.007