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

We propose bootstrap implementations of the asymptotic Wald, likelihood ratio and Lagrange multiplier tests for the … that neither the asymptotic tests nor the analogues of these which obtain from using a standard i.i.d. bootstrap admit … wild bootstrap principle do. An heteroskedasticity-robust Wald test, based around a sandwich estimator of the variance, is …

theta_n, its bootstrap approximation, and the Bayesian posterior for all agree asymptotically. It is shown that whenever g … is Lipschitz, though not necessarily differentiable, the posterior distribution of g(theta) and the bootstrap … distribution of g(theta_n) coincide asymptotically. One implication is that Bayesians can interpret bootstrap inference for g …

regions with an efficient bootstrap procedure that runs in linear computing time. The method can be applied to the empirical …