Bootstrap tests are tests for which the significance level is calculated by some sort of bootstrap procedure, which may be parametric or nonparametric. We provide a theoretical framework in which to study the size distorsions of bootstrap P values. We show that, in many circumstances, the size...

Most confidence intervals, whether based on asymptotic theory or the bootstrap, are implicitly based on inverting a Wald test. Since Wald test statistics are not invariant under nonlinear reparametrizations of the restrictions they test, confidence intervals based on them are not invariant...

Le test J applique aux modeles de regression non emboites a souvent des performances qui sont mauvaises pour la version asymptotique du test, mais tres bonnes pour la forme bootstrap. On donne une analyse theorique qui explique les deux phenomenes. On propose une version modifiee du test qui,...

In this paper we develop a general strategy for studying the effect on unbiased, nearest-neighbor walks of opening up or blocking a trap or neural site on a d-dimensional lattice.

In this paper we propose a form of semi-nonparametric regression based on wavelet analysis, and demonstrate its empirical utility in the context of commodity price behavior.

We show that, in many circumstances, the size distortion of a bootstrap P value for a test will be one whole order of magnitude smaller than that of the corresponding asymptotic P value. We also show that, at least in the parametric case, the magnitude of the distorsion will depend on the shape...