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A bivariate F distribution with marginals on arbitrary numerator and denominator degrees of freedom, and related bivariate beta and t distributions

机译:具有任意分子和分母自由度边际的双变量F分布以及相关的双变量beta和t分布

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摘要

The classical bivariate F distribution arises from ratios of chi-squared random variables with common denominators. A consequent disadvantage is that its univariate F marginal distributions have one degree of freedom parameter in common. In this paper, we add a further independent chi-squared random variable to the denominator of one of the ratios and explore the extended bivariate F distribution, with marginals on arbitrary degrees of freedom, that results. Transformations linking F, beta and skew t distributions are then applied componentwise to produce bivariate beta and skew t distributions which also afford marginal (beta and skew t) distributions with arbitrary parameter values. We explore a variety of properties of these distributions and give an example of a potential application of the bivariate beta distribution in Bayesian analysis.
机译:经典的二元变量F分布是由具有公分母的卡方随机变量的比率得出的。随之而来的缺点是其单变量F边际分布共有一个自由度参数。在本文中,我们将另外一个独立的卡方随机变量添加到其中一个比率的分母上,并探索扩展的双变量F分布,并在任意自由度上具有边际。然后,将F,β和偏斜t分布链接在一起的转换以分量方式应用,以生成双变量β和偏斜t分布,它们也提供具有任意参数值的边际(β和偏斜t)分布。我们探索了这些分布的各种性质,并举例说明了双变量β分布在贝叶斯分析中的潜在应用。

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