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A convex/log-concave correlation inequality for Gaussian measure and an application to abstract Wiener spaces

机译:高斯测度的凸/对数-凹相关不等式及其在抽象维纳空间中的应用

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摘要

This paper deals with a generalization of a result due to Brascamp and Lieb which states that in the space of probabilities with log-concave density with respect to a Gaussian measure on this Gaussian measure is the one which has strongest moments. We show that this theorem remains true if we replace x α by a general convex function. Then, we deduce a correlation inequality for convex functions quite better than the one already known. Finally, we prove results concerning stochastic analysis on abstract Wiener spaces through the notion of approximate limit.
机译:本文对Brascamp和Lieb的结果进行了概括,指出在该高斯测度上,相对于高斯测度,在具有对数凹凹密度的概率空间中,矩最强。我们证明,如果用一般凸函数代替xα,则该定理仍然成立。然后,我们推论出凸函数的相关不等式要比已知函数好得多。最后,我们通过近似极限的概念证明了抽象维纳空间的随机分析结果。

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