对称矩阵上Riesz概率分布的高斯表示

IF 1.4 4区 数学 Q2 STATISTICS & PROBABILITY Asta-Advances in Statistical Analysis Pub Date : 2022-03-06 DOI:10.1007/s10182-022-00436-w
Abdelhamid Hassairi, Fatma Ktari, Raoudha Zine
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引用次数: 0

摘要

对称矩阵上的Riesz概率分布是Wishart分布的一个重要推广。它是由广义幂的拉普拉斯变换定义的。基于一些Wishart分布是由多元高斯分布的均值表示的事实,证明了一些不一定是Wishart的Riesz概率分布也可以由缺失数据的高斯样本的均值表示。作为推论,我们推导出逆Riesz分布的高斯表示,并给出了它的期望。在模拟研究中对结果进行了评估。
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On the Gaussian representation of the Riesz probability distribution on symmetric matrices

The Riesz probability distribution on symmetric matrices represents an important extension of the Wishart distribution. It is defined by its Laplace transform involving the notion of generalized power. Based on the fact that some Wishart distributions are presented by the mean of the multivariate Gaussian distribution, it is shown that some Riesz probability distributions which are not necessarily Wishart are also presented by the mean of Gaussian samples with missing data. As a corollary, we deduce a Gaussian representation of the inverse Riesz distribution and we give its expectation. The results are assessed in simulation studies.

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来源期刊
Asta-Advances in Statistical Analysis
Asta-Advances in Statistical Analysis 数学-统计学与概率论
CiteScore
2.20
自引率
14.30%
发文量
39
审稿时长
>12 weeks
期刊介绍: AStA - Advances in Statistical Analysis, a journal of the German Statistical Society, is published quarterly and presents original contributions on statistical methods and applications and review articles.
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