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首页> 外文期刊>Journal of Theoretical Probability >Uniform Comparison of Tails of (Non-Symmetric) Probability Measures and Their Symmetrized Counterparts with Applications
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Uniform Comparison of Tails of (Non-Symmetric) Probability Measures and Their Symmetrized Counterparts with Applications

机译:(非对称)概率测度的尾巴及其对称对等的均匀比较及其应用

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Let ( $mathbb{B}$ , $|cdot|$ ) be a separable Banach space and let $mathcal{M}$ be a class of probability measures on $mathbb{B}$ , and let $bar{mu}$ denote the symmetrization of $muinmathcal{M}$ . We provide two sufficient conditions (one in terms of certain quantiles and the other in terms of certain moments of $|cdot|$ relative to μ and $bar{mu}$ , $muinmathcal{M}$ ) for the “uniform comparison” of the μ and $bar{mu}$ measure of the complements of the closed balls of $mathbb{B}$ centered at zero, for every $muinmathcal{M}$ . As a corollary to these “tail comparison inequalities,” we show that three classical results (the Lévy-type Inequalities, the Kwapień-Contraction Inequality, and a part of the It?–Nisio Theorem) that are valid for the symmetric (but not for the general non-symmetric) independent $mathbb{B}$ -valued random vectors do indeed hold for the independent random vectors whose laws belong to any $mathcal{M}$ which satisfies one of the two noted conditions and which is closed under convolution. We further point out that these three results (respectively, the tail comparison inequalities) are valid for the centered log-concave, as well as, for the strictly α-stable (or the more general strictly (r, α) -semistable) α ≠ 1 random vectors (respectively, probability measures). We also present several examples which we believe form a valuable part of the paper.
机译:令($ mathbb {B} $,$ | cdot | $)为可分离的Banach空间,令$ mathcal {M} $为$ mathbb {B} $上的一类概率测度,并令$ bar {mu} $表示$ muinmathcal {M} $的对称化。我们提供了两个足够的条件(一个相对于分位数而言,一个相对于μ和$ bar {mu} $,$ muinmathcal {M} $)相对于$ | cdot | $的矩)来进行“均匀比较”对于每个$ muinmathcal {M} $,对$ mathbb {B} $的闭合球的补码的μ和$ bar {mu} $的度量的值以零为中心。作为这些“尾部比较不等式”的推论,我们证明了对对称性有效的三个经典结果(Lévy型不等式,Kwapień-收缩不等式和It?-Nisio定理的一部分)对于一般的非对称)独立$ mathbb {B} $值随机向量的确适用于其定律属于任何$ mathcal {M} $且满足以下两个条件之一且在以下条件下闭合的独立随机向量卷积。我们进一步指出,这三个结果(分别是尾部比较不等式)对于居中对数凹面以及严格α稳定(或更严格地说是严格(r,α)-半稳定)的α有效≠1个随机向量(分别为概率量度)。我们还提供了一些示例,我们认为它们是本文的重要组成部分。

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