在本文中,我们开发了一个新的多元分布,该分布适用于计数数据,称为树p´olya拆分。该类是由沿固定分区树的单变量分布和单数多变量分布的组合而产生的。已知的分布,包括Dirichlet-Multinomial,广义的Dirichlet-Multinomial和Dirichlet-Tree多项式,是此类中的特殊情况。正如我们将要证明的那样,这些分布是灵活的,可以在观测水平上建模复杂的依赖性结构(正,负或空)。具体来说,我们通过主要关注边缘分布,段落矩和依赖性结构(协方差和相关性)来介绍树p´olya分裂分布的理论特性。A dataset of abundance of Trichoptera is used, on one hand, as a benchmark to illustrate the theoretical properties developed in this article, and on the other hand, to demonstrate the interest of these types of models, notably by comparing them to other approaches for fitting multivariate data, such as the Poisson-lognormal model in ecology or singular multivariate distributions used in microbiome.
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