Pearson's correlation is one of the most common measures of linear dependence. Recently, Bernardo (11th International Workshop on Objective Bayes Methodology, 2015) introduced a flexible class of priors to study this measure in a Bayesian setting. For this large class of priors, we show that the (marginal) posterior for Pearson's correlation coefficient and all of the posterior moments are analytic. Our results are available in the open‐source software package JASP.

中文翻译：

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Pearson 相关系数的后验分析

Pearson 相关性是最常见的线性相关性度量之一。最近，Bernardo（第 11 届目标贝叶斯方法国际研讨会，2015 年）引入了一类灵活的先验，以在贝叶斯设置中研究该度量。对于这一大类先验，我们表明 Pearson 相关系数的（边际）后验和所有后验矩都是解析的。我们的结果可以在开源软件包 JASP 中找到。