Incorporating a change-point estimator when bootstrapping the empirical distribution of a stationary process

The moving block bootstrap can be used to determine critical values for test statistics used to detect a change-point in the marginal distribution of a stationary time series. We examine the impact of incorporating an estimator of the change-point when centering the bootstrap blocks and establish conditions under which the bootstrapped test statistics remain stochastically bounded regardless of whether or not a change is present.

Automated summary

The paper examines the impact of incorporating an estimator of the change-point when centering the bootstrap blocks and establishes conditions under which the bootstrapped test statistics remain stochastically bounded regardless of the presence of a change.