The aim of this paper is to define and investigate outlier-proneness for multivariate distributions. This is done by using a concept of ordering multivariate data based on isobar-surfaces, which yields an utmost analogy of the results to the univariate case.

The aim of this paper is to define and investigate outlier-proneness for multivariate distributions. This is done by using a concept of ordering multivariate data based on isobar-surfaces, which yields an utmost analogy of the results to the univariate case.

A definition of the ordering of a multivariate sample--based on the isobar surfaces--is used in order to obtain limit laws for the extreme values of a multidimensional sample.

The aim of this paper is to define and investigate outlier-proneness for multivariate distributions. This is done by using a concept of ordering multivariate data based on isobar-surfaces, which yields an utmost analogy of the results to the univariate case.