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A review on strong convergence of weighted sums of random elements based on Wasserstein metrics
Authors:Juan A Cuesta
Institution:

Departamento de Matemáticas, Estadística y Computacion, Universidad de Cantabria, 39005 Santander, Spain

Departamento de Estadística, Universidad de Valladolid, 47002 Valladolid, Spain

Abstract:In a previous paper the authors proposed a simple method to extend results about almost sure convergence for weighted sums of real random variables to the case of Banach-valued random elements. The method arises from the extension of Skorohod's Representation Theorem for weakly convergent sequences due to Blackwell and Dubins, applied to the general framework of weakly equivalent tight sequences of probability measures. This provides a scheme which permits us to handle separately a problem that behaves like the Glivenko-Cantelli Theorem and a question on uniform integrability which generally is reduced to the real valued version of the general problem to be solved.

In this paper we prove that Wasserstein's metrics can play the same role as Skorohod's Representation Theorem in the preceding scheme. We also show that our method can be applied to obtain results with respect to various summability methods (Abel, Euler, …) even in the case in which the ‘weights’ are linear operators.

Keywords:Strong Law of Large Numbers  pairwise independence  Glivenko-Cantelli Theorem  weighted sums  equivalence of sequences of distributions  random elements in Banach spaces  strong convergence  linear operators
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