3 papers
stat.ME2026
Univariate-Guided Sparse Regression for Biobank-Scale High-Dimensional Omics Data
Joshua Richland, Tuomo Kiiskinen, William Wang +5
We present a scalable framework for computing polygenic risk scores (PRS) in high-dimensional genomic settings using the recently introduced Univariate-Guided Sparse Regression (un…
stat.ME2025
Univariate-Guided Sparse Regression
Sourav Chatterjee, Trevor Hastie, Robert Tibshirani
In this paper, we introduce ``UniLasso'' -- a novel statistical method for sparse regression. This two-stage approach preserves the signs of the univariate coefficients and leverag…
stat.ME2025
Pre-validation Revisited
Jing Shang, Sourav Chatterjee, Trevor Hastie +1
Pre-validation is a way to build prediction model with two datasets of significantly different feature dimensions. Previous work showed that the asymptotic distribution of the resu…