Basic Sequences in the Dual of a Fréchet Space

In this paper we study some properties of basic sequences in the dual of a Fréechet space. As a consequence we obtain that if E is a Fréechet space with the property that for each closed subspace F of E and each bounded subset B of E/F there is a bounded subset A of E with φ(A) = B, where φ denotes the canonical surjection of E onto E/F, then one of the following conditions is at least satisfied: 1. E is a Banach space, 2. E is a Schwartz space, 3. E is the product of a Banach space by ω. Finally, we also obtain some results concerning totally reflexive spaces.     

A Fréchet-Optimal Strengthening of the Dawson-Sankoff Lower Bound

This paper proposes a lower bound for the probability that at least one out of arbitrary events occurs. The information used consists of the first- and second- degree Bonferroni summations in conjunction with and , where is the probability that exactly one event occurs and is the probability that all events occur. We prove that the proposed bound is a Fréchet optimal lower bound, which is a criterion difficult to achieve in general. The two additional non-negative terms used in the proposed bound make it at least as good as the Dawson–Sankoff lower bound, a Fréchet optimal degree two lower bound using the first- and second- degree Bonferroni summations only. A numerical example is presented to illustrate that in some cases, the improvement can be substantial. *Part of the work of this author was done as Visiting Scholar, 2004, at the University of Sydney.     

Characterizations of counter-monotonicity and upper comonotonicity by (tail) convex order

In this paper, we characterize counter-monotonic and upper comonotonic random vectors by the optimality of the sum of their components in the senses of the convex order and tail convex order respectively. In the first part, we extend the characterization of comonotonicity by  Cheung (2010) and show that the sum of two random variables is minimal with respect to the convex order if and only if they are counter-monotonic. Three simple and illuminating proofs are provided. In the second part, we investigate upper comonotonicity by means of the tail convex order. By establishing some useful properties of this relatively new stochastic order, we prove that an upper comonotonic random vector must give rise to the maximal tail convex sum, thereby completing the gap in  Nam et al. (2011)’s characterization. The relationship between the tail convex order and risk measures along with conditions under which the additivity of risk measures is sufficient for upper comonotonicity is also explored.     

Bootstrap estimation of the asymptotic variances of statistical functionals

A modified bootstrap estimator of the asymptotic variance of a statistical functional is studied. The modified bootstrap variance estimator circumvents the problem of the original bootstrap when the population distribution has heavy tails, and requires less stringent conditions for its consistency than the ordinary bootstrap variance estimator. The consistency of the modified bootstrap variance estimator is established for differentiable statistical functionals.     

Geometric properties of Fréchet spaces and selection of basis sequences

For an arbitrary nuclear Fréchet spaceE possessing the well-known geometric propertiesD ₁ (DN) and Ω, certain sequences of functionals and elements with power-type estimates of the norms are selected. With the help of these objects, two isomorphic spacesK ₁ andK ₂ of power series of infinite type and continuous mapsJ ₂: K₂→E andJ ₁: E→K₁ are defined. Under some auxiliary conditions, it is proved that the_i are isomorphisms and the spaceE possesses a basis. Translated fromMatematicheskie Zametki, Vol. 66, No. 1, pp. 102–111, July, 1999.     

Characterization of comonotonicity using convex order

It is well known that if a random vector with given marginal distributions is comonotonic, it has the largest sum with respect to the convex order. In this paper, we prove that the converse is also true, provided that each marginal distribution is continuous.     

The exactness of the projective limit functor on the category of quotients of Frechet spaces

We give conditions under which the functor projective limit is exact on the category of quotients of Fréchet spaces of L.Waelbroeck [18].     

On some Fermat rules for set-valued optimization problems

The aim of this article is to obtain necessary optimality conditions for Pareto minima in set-valued optimization problems. We employ a new method to derive generalized Fermat rules for set-valued optimization. This method is based on openness results for multifunctions and allows recovery of a large number of results and, at the same time, getting several new ones.