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

-sided. In such problems, power gains can be obtained for bootstrap multiple testing procedures in scenarios where some of the …

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 …

manner, we propose a model-based (semiparametric)bootstrap method to approximate critical values of the test and verify its …

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

rejection regions can be calculated by a simple parametric bootstrap procedure, when the sample size is small. The size and …

-defined. Several bootstrap procedures are proposed. They alleviate the problem and allow reliable inference when the instruments are …

the increasing need for faster, and more efficient and scalable, permutation test and bootstrap algorithms. Seven … bootstrap and six permutation test algorithms coded in SAS (the largest privately owned software firm globally) are compared …. The fastest algorithms (“OPDY” for the bootstrap, “OPDN” for permutation tests) are new, use no modules beyond Base SAS …