An omnibus test for spherical symmetry in R2 is proposed, employing localized empirical likelihood. The thus obtained test statistic is distribution-free under the null hypothesis. The asymptotic null distribution is established and critical values for typical sample sizes, as well as the...

Consider the nonparametric regression model Y = m(X)+e, where the function m is smooth, but unknown. We construct tests for the independence of e and X, based on n independent copies of (X; Y). The testing procedures are based on differences of neighboring Y's. We establish asymptotic results...

Consider a random sample from a continuous multivariate distribution function F with copula C. In order to test the null hypothesis that C belongs to a certain parametric family, we construct an under H0 asymptotically distribution-free process that serves as a tests generator. The process is a...

Let (X1, Y1), … , (Xn, Yn) be an i.i.d. sample from a bivariate distribution function that lies in the max-domain of attraction of an extreme value distribution. The asymptotic joint distribution of the standardized component-wise maxima max( Xi) and max(Yi) is then characterized by the...

A novel, general two-sample hypothesis testing procedure is established for testing the equality of tail copulas associated with bivariate data. More precisely, using an ingenious transformation of a natural two-sample tail copula process, a test process is constructed, which is shown to...

We introduce generalized Probability-Probability (P-P) plots in order to study the one-sample goodness-of-fit problem and the two-sample problem, for real valued data. These plots, that are constructed by indexing with the class of closed intervals, globally preserve the properties of classical...

Consider n i.i.d. random vectors on R2, with unknown, common distribution function F. Under a sharpening of the extreme value condition on F, we derive a weighted approximation of the corresponding tail copula process. Then we construct a test to check whether the extreme value condition holds...