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...

Associated with every popular nonlinear estimationmethod is at least ont "artificial" linear regression. We define an artificial regression in terms of three conditions that it must satisfy. Then we show how artificial regressions can be useful for numerical optimization, testing hypotheses, and...