A Bayesian Functional Accelerated Failure-Time Model with Varying Effects Correcting for Measurement Error
校正测量误差的变效应贝叶斯函数型加速失效时间模型
Functional data collected as continuously observed trajectories arise naturally in many biomedical settings, and a key inferential goal is understanding how such functional covariates relate to time-to-event outcomes while allowing that relationship to vary across subgroups defined by scalar characteristics. Existing frequentist approaches to functional accelerated failure-time (AFT) models struggle to flexibly capture the joint, nonlinear influence of scalar covariates and…