AN UPPER BOUND ON THE EXPECTATION OF SIMPLICIAL FUNCTIONS OF MULTIVARIATE RANDOM-VARIABLES

We introduce an upper bound on the expectation of a special class of sublinear functions of multivariate random variables defined over the entire Euclidean space without an independence assumption. The bound can be evaluated easily requiring only the solution of systems of linear equations thus permitting implementations in high-dimensional space. Only knowledge on the underlying distribution means and second moments is necessary. We discuss pertinent techniques on dominating general sublinear function, by using simpler sublinear and polyhedral functions and second order quadratic functions.