A Primal Dual Active Set with Continuation Algorithm for ℓ0-penalized High-dimensional Accelerated Failure Time Model

The accelerated failure time model has garnered attention due to its intuitive linear regression interpretation and has been successfully applied in fields such as biostatistics, clinical medicine, economics, and social sciences.This paper considers a weighted least squares estimation method with an 0-penalty based on right-censored data in a high-dimensional setting.For practical implementation, we adopt an efficient primal dual active set algorithm and utilize a continuous strategy to select t