Strong approximations for the general bootstrap of empirical processes with applications in selected topics of nonparametric statistics
Abstract
The purpose of this note is to provide an approximation for the generalized bootstrapped empirical process achieving the rate in [38]. The proof is based on the same arguments used in [36]. As a conséquence, we establish an approximation of the bootstrapped kernel distribution estimation. Purthermore, our results are applied to two-sample testing procedures as well as to change-point problems. We end with establishing strong approximations of the bootstrapped empirical process when the parameters are estimated.
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