and second order stochastic dominance in the general k-prospect case. Our method is based on subsampling bootstrap. We …

methods (i.e., the asymptotic distribution versus the bootstrap) have been proposed. In this paper, we compare these methods …

composite null hypotheses of SD orders. This is in contrast to simulation and bootstrap-based techniques that do so, resulting …

We introduce a new, factor based bootstrap approach which is robust under heteroskedastic error terms for inference in … functional coefficient models. Modeling the functional coefficient parametrically, the bootstrap approximation of an F statistic …, factor based bootstrap inference outperforms the wild bootstrap and pairs bootstrap approach according to its size features …

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 …

coverage for small sample sizes, a simple bootstrap procedure is designed based on the leading term of the Bahadur … demonstrated that the bootstrap procedure considerably outperforms the asymptotic bands in terms of coverage accuracy. Finally, the … bootstrap confidence corridors are used to study the efficacy of the National Supported Work Demonstration, which is a …

tails and time dependence in the return data. In particular, we will promote a studentized time series bootstrap procedure …