论文标题

概括de finetti-hewitt-传播定理

Generalizing the de Finetti--Hewitt--Savage theorem

论文作者

Alam, Irfan

论文摘要

如果随机变量在索引排列下是不变的,则称为\ textit {可交换}。 de Finetti定理的原始表述粗略地说,任何可交换序列的$ \ {0,1 \} $ - 有价值的随机变量都可以视为独立且分布的序列的混合物。 Hewitt和Savage能够获得相同的结论,以在某些拓扑条件下在更一般的状态空间中以随机变量为单位的可交换序列。 使用非标准分析中的工具,我们证明,在任何Hausdorff状态空间中采用值的ra-Distribed随机变量的可交换序列必须表示为自变和相同分布的随机变量的混合物。 我们对这项工作的介绍遵循\ textit {讲义}的风格,用于广泛的研究生级数学受众 - 手稿的主体始于历史上对问题的扎根介绍,预示着通过一系列附录开发的我们的技术。这些技术用于在引言后的简短部分中提供我们主要结果的独立证明。 我们在第一个附录中为非标准分析提供了一个独立的哲学动机介绍,从而使第一课程衡量了理论概率和点集拓扑,这是工作的唯一前提。这项简介旨在发展一些有关该主题的新意识形态,这些意识形态可能引起数学家,哲学家和数学教育者的感兴趣。其余附录的一个亮点是在任意Hausdorff空间的所有概率度量的空间中对Prokhorov定理的新概括。

A sequence of random variables is called \textit{exchangeable} if its joint distribution is invariant under permutations of indices. The original formulation of de Finetti's theorem roughly says that any exchangeable sequence of $\{0,1\}$-valued random variables can be thought of as a mixture of independent and identically distributed sequences. Hewitt and Savage were able to obtain the same conclusion for exchangeable sequences of random variables taking values in more general state spaces under some topological conditions. Using tools from nonstandard analysis we prove that an exchangeable sequence of Radon-distributed random variables taking values in any Hausdorff state space must be representable as a mixture of sequences of independent and identically distributed random variables. Our presentation of this work follows the style of \textit{lecture notes} intended for broad graduate-level mathematical audiences -- the main body of the manuscript starts with a historically grounded introduction to the problem, foreshadowing our techniques that are developed via a series of appendices. These techniques are used to provide self-contained proofs of our main results in a short section following the introduction. We have provided a self-contained philosophically motivated introduction to nonstandard analysis in the first appendix, thus rendering first courses in measure theoretic probability and point-set topology as the only prerequisites for the work. This introduction aims to develop some new ideologies about the subject that might be of interest to mathematicians, philosophers, and mathematics educators alike. One highlight of the rest of the appendices is a new generalization of Prokhorov's theorem in the setting of the space of all probability measures on arbitrary Hausdorff spaces.

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