Confidence intervals for high-dimensional accelerated failure time models under measurement errors.

In high-dimensional survival analysis, sparse learning is critically important, as evidenced by applications in molecular biology, economics, and climate science. Despite rapid advances on sparse modeling of survival data, achieving valid statistical…

Preview only. Read the full abstract at the source