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引用次数: 0
摘要
假设 X 是一个具有有限第二矩的随机变量。我们研究不等式\(P\{|X-\textrm{E}[X]|\le \sqrt{\textrm{Var}(X)}\}ge P\{|Z|\le 1\}\),其中 Z 是标准正态随机变量。我们证明了这个不等式对许多熟悉的无限可分连续分布都成立,包括拉普拉斯分布、甘贝尔分布、对数分布、帕累托分布、无限可分韦布尔分布、对数正态分布、Student's t 分布和反高斯分布。给出的数值结果表明,带连续性修正的不等式也适用于某些无限可分离散分布。
Variation comparison between infinitely divisible distributions and the normal distribution
Let X be a random variable with finite second moment. We investigate the inequality: \(P\{|X-\textrm{E}[X]|\le \sqrt{\textrm{Var}(X)}\}\ge P\{|Z|\le 1\}\), where Z is a standard normal random variable. We prove that this inequality holds for many familiar infinitely divisible continuous distributions including the Laplace, Gumbel, Logistic, Pareto, infinitely divisible Weibull, Log-normal, Student’s t and Inverse Gaussian distributions. Numerical results are given to show that the inequality with continuity correction also holds for some infinitely divisible discrete distributions.
期刊介绍:
The journal Statistical Papers addresses itself to all persons and organizations that have to deal with statistical methods in their own field of work. It attempts to provide a forum for the presentation and critical assessment of statistical methods, in particular for the discussion of their methodological foundations as well as their potential applications. Methods that have broad applications will be preferred. However, special attention is given to those statistical methods which are relevant to the economic and social sciences. In addition to original research papers, readers will find survey articles, short notes, reports on statistical software, problem section, and book reviews.