2 papers
stat.ME2026
Adaptive Long-Run Variance Thresholding for Sparse Covariance Estimation in High-Dimensional Time Series
Wenhao Zhang, Zhaoxing Gao
Estimating a sparse covariance matrix is a fundamental problem in high-dimensional statistics. However, thresholding methods developed for independent data are generally not direct…
stat.ME2026
Forward Regression via Gram-Schmidt Orthogonalization for Ultra-High Dimensional Linear Models
Jialuo Chen, Zhaoxing Gao, Yifan Jiang +1
Forward regression is a classical and effective tool for variable screening in ultra-high dimensional linear models, but its standard projection-based implementation can be computa…