We show that many uniformly convex bodies have Gaussian marginals in most directions in a strong sense, which takes into account the tails of the distributions. These include uniformly convex bodies with power type 2, and power type p > 2 with some additional type condition. In particular, all unit-balls of subspaces of Lp for 1 < p < ∞ have Gaussian marginals in this strong sense. Using the we...

The aim of this paper is to develop a conjugate duality theory for convex set–valued maps. The basic idea is to understand a convex set–valued map as a function with values in the space of closed convex subsets of R. The usual inclusion of sets provides a natural ordering relation in this space. Infimum and supremum with respect to this ordering relation can be expressed with aid of union and i...

Stone-Weierstrass-type theorems for groups of group-valued functions with discrete range or discrete domain are obtained. We study criteria for a subgroup of the group of continuous functions C(X,G) (X compact, G a topological group) to be uniformly dense. These criteria are based on the existence of so-called condensing functions, where a continuous function φ : G → G is said to be condensing ...

The function Df , called the Bregman distance associated with f , is always well defined because ∂f(x) is nonempty and bounded, for all x ∈ X (see, e.g., [22]), so that the infimum in (1.1) cannot be −∞. It is easy to check that Df (x, y) ≥ 0 and that Df (x, x) = 0, for all x, y ∈ X. If f is strictly convex then Df (x, y) = 0 only when x = y. For t ∈ [0,∞) and z ∈ X let U(z, t) = {x ∈ X : ‖x− z...

In this article, we use two concepts, measure of non-compactness and Meir-Keeler condensing operators. The measure of non-compactness has been applied for existence of solution nonlinear integral equations, ordinary differential equations and system of differential equations in the case of finite and infinite dimensions by some authors. Also Meir-Keeler condensing operators are shown in some pa...

For finding zeros or fixed points of set-valued maps, the fact that the space of convex, compact, nonempty sets of R is not a vector space presents a major disadvantage. Therefore, fixed point iterations or variants of Newton’s method, in which the derivative is applied only to a smooth single-valued part of the set-valued map, are often applied for calculations. We will embed the set-valued ma...

This paper addresses the problem of testing simple hypotheses about the mean of a bivariate normal distribution with identity covariance matrix against restricted alternatives. The LRTs and their power functions for such types of hypotheses are derived. Furthermore, through some elementary calculus, it is shown that the power function of the LRT satisfies certain monotonicity and symmetry p...

The probability measures on compact Hausdorff spaces K form a compact convex subset PK of the space of measures with the vague topology. Every continuous map f : K → L of compact Hausdorff spaces induces a continuous affine map Pf : PK → PL extending P. Together with the canonical embedding ε : K → PK associating to every point its Dirac measure and the barycentric map β associating to every pr...

Various types of φA-spaces (X,D; {φA}A∈〈D〉) are simply G-convex spaces. Various types of generalized KKM maps on φA-spaces are simply KKM maps on G-convex spaces. Therefore, our G-convex space theory can be applied to various types of φAspaces. As such examples, we obtain KKM type theorems and a very general fixed point theorem on φA-spaces. RESUMEN Varios tipos de φA-espacios (X,D; {φA}A∈〈D〉) ...

Convexification is a fundamental technique in (mixed-integer) nonlinear optimization and many convex relaxations are parametrized by variable bounds, i.e., the tighter the bounds, the stronger the relaxations. This paper studies how bound tightening can improve convex relaxations for power network optimization. It adapts traditional constraintprogramming concepts (e.g., minimal network and boun...