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Weak convergence of measures: applications in probability

by Patrick Billingsley

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A treatment of the convergence of probability measures from the foundations to applications in limit theory for dependent random variables. Mapping theorems are proved via Skorokhod's representation theorem; Prokhorov's theorem is proved by construction of a content. The limit theorems at the conclusion are proved under a new set of conditions that apply fairly broadly, but at the same time make possible relatively simple proofs.… (more)
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The pages that follow are a record of ten lectures I gave during September of 1970 at a Regional Conference in the Mathematical Sciences at Iowa City, sponsored by the Conference Board of the Mathematical Sciences and the University of Iowa with support from the National Sciences Foundation.
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This is one way of requiring that the past and future do not unduly influence each other.
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A treatment of the convergence of probability measures from the foundations to applications in limit theory for dependent random variables. Mapping theorems are proved via Skorokhod's representation theorem; Prokhorov's theorem is proved by construction of a content. The limit theorems at the conclusion are proved under a new set of conditions that apply fairly broadly, but at the same time make possible relatively simple proofs.

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