functionals of kernel-type estimators (1 < p < ∞) 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 …

using the bootstrap. An empirical application illustrates the usefulness of shape restrictions for carrying out …

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

(g) can be carried out by using by using the bootstrap. An empirical application illustrates the usefulness of shape …

distribution of a suitable estimator θ^n, its bootstrap approximation, and the Bayesian posterior for θ all agree asymptotically …(θ) and the bootstrap distribution of g(θ^n) coincide asymptotically. One implication is that Bayesians can interpret … bootstrap inference for g(θ) as approximately valid posterior inference in a large sample. Another implication−built on known …

the distribution of a suitable estimator theta_n, its bootstrap approximation, and the Bayesian posterior for theta all … distribution of g(theta) and the bootstrap distribution of theta_n coincide asymptotically. One implication is that Bayesians can … interpret bootstrap inference for g(theta) as approximately valid posterior inference in a large sample. Another implication …

methods for selecting bandwidths that under- or oversmooth. This paper extends the bootstrap method of Hall and Horowitz (2013 …) for conditional mean functions to conditional quantile functions. The paper also shows how the bootstrap method can be … used to obtain uniform confidence bands. The bootstrap method uses only bandwidths that are selected by standard methods …

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 …