We remark that the Dirichlet distribution with a uniform parameter of one can be easily approximated by independent exponential distribution. We use this block bootstrap as a default of the NeuBoots in sequel. We shall rigorously investigate asymptotic equivalence between the blocked bootstrap and the non-blocked bootstrap. To ease the explanation for theory, we introduce some notation here. Recall that the notation is introduced in Section 2 .[

Bootstrapping has been a primary tool for ensemble and uncertainty quantification in machine learning and statistics.