The paper investigates how the particular choice of residuals used in a bootstrap-based testing procedure affects the properties of the test. The properties of the tests are investigated both under the null and under the alternative. It is shown that for non-pivotal test statistics, the method...

We consider finite-order moving average and nonlinear autoregressive processes with no parametric assumption on the error distribution, and present a kernel density estimator of a bootstrap series that estimates their marginal densities root-n consistently. This is equal to the rate of the best...

A construction of p-values for hypothesis tests based on subsampling and the related m out of n bootstrap is introduced. The p-values are based on a modification of the usual subsampling hypothesis tests that involves an appropriate centering of the subsampled or bootstrapped test statistics as...

The problem of estimating nonparametric regression with associated confidence intervals is addressed. It is shown that through appropriate choice of infinite order kernel, it is possible to construct bootstrap confidence intervals which do not require either explicit bias correction or...