We use a subsample bootstrap method to get a consistent estimate of the asymptotically optimal choice of the …

different bootstrap tests. In the context of static linear regression modelstwo of these are shown to have serious size and …

determined with a permutation procedure and a parametric bootstrap in the testsfor serial independence and linearity …

find that, by using the bootstrap technique to estimate confidence intervals, we can point at the uncertainty of the …

We consider theoretical bootstrap coupling techniques for nonparametric robust smoothers and quantile regression, and … verify the bootstrap improvement. To cope with curse of dimensionality, a variant of coupling bootstrap techniques are …. Our bootstrap method can be used in many situations like constructing con dence intervals and bands. We demonstrate the …

bootstrap algorithm to implement the proposed test and show its asymptotic validity. The proposed test procedure can apply to …

functionals of kernel-type estimators (1 < p < É) and is easy to implement in general, mainly due to its recourse to the bootstrap … method. The bootstrap procedure is based on nonparametric bootstrap applied to kernel-based test statistics, with estimated … 'contact sets'. We provide regularity conditions under which the bootstrap test is asymptotically valid uniformly over a large …