Abstract
This is a study of the behaviors of the naive bootstrap and the Bayesian bootstrap clones designed to approximate the sampling distribution of the Aalen–Johansen estimator of a non-homogeneous censored Markov chain. The study shows that the approximations based on the Bayesian bootstrap clones and the naive bootstrap are first-order asymptotically equivalent. The two bootstrap methods are illustrated by a marketing example, and their performance is validated by a Monte Carlo experiment.
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