This book offers a comprehensive framework for mastering the complexities of learning high-dimensional sparse graphical models through the use of conditional independence tests. These tests are ...

In high-dimensional data analysis, we propose a sequential model averaging (SMA) method to make accurate and stable predictions. Specifically, we introduce a hybrid approach that combines a sequential ...

Categorical distinctions remain vital for clarity, prognosis, and treatment in personality disorder diagnosis.

In the nanoscale world, a tiny little bit can mean a lot. Working with large-scale computer simulations, a team of scientists that included Xiao Cheng Zeng, professor of chemistry at the University of ...

Motivated by ultrahigh-dimensional biomarkers screening studies, we propose a model-free screening approach tailored to censored lifetime outcomes. Our proposal is built upon the introduction of a new ...