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

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

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 …

distribution depend on unknown nuisance parameters. A bootstrap method is used to obtain more reliable inference. The regularized …

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

our approach bootstrap fails in practice and theory. Instead, we propose a subsampling procedure with automatic parameter …