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arxiv: 0907.2501 · v2 · submitted 2009-07-15 · 🧮 math.PR

On the structure of Gaussian random variables

classification 🧮 math.PR
keywords gaussianrandombetagivenprobabilityresultspacevariable
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We study when a given Gaussian random variable on a given probability space $(\Omega, {\cal{F}}, P) $ is equal almost surely to $\beta_{1}$ where $\beta $ is a Brownian motion defined on the same (or possibly extended) probability space. As a consequences of this result, we prove that the distribution of a random variable (satisfying in addition a certain property) in a finite sum of Wiener chaoses cannot be normal. This result also allows to understand better some characterization of the Gaussian variables obtained via Malliavin calculus.

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