Technology, Artificial Intelligence, Machine Learning, Data Science, Deep Learning.
penalty, designed for left-truncated and interval-censored time-to-event data. We develop a custom Markov chain Monte Carlo sampler for efficient estimation, and investigate the impact of various methods of penalty tuning and thresholding for variable selection. We present a simulation study