论文标题

连续分布混合物中异质性的乘法分解

Multiplicative Decomposition of Heterogeneity in Mixtures of Continuous Distributions

论文作者

Nunes, Abraham, Alda, Martin, Trappenberg, Thomas

论文摘要

系统的异质性(\ textit {多样性})是其事件空间的有效尺寸,可以使用rényi家族指数(也称为生态学中的山丘数或经济学中的汉娜·卡伊(Hannah-Kay)指数)来量化,这是由弹性参数$ q q \ egeq 0 $ q。在这些指数下,复合系统($γ$ - 异质性)的异质性分解为异质性,这是由变化\ textit {ins}和\ textit {}组件子系统(分别$α$ - - 和$β$ - 和$β$ - 高元素性)引起的。由于组件子系统的平均异质性不应大于合并系统的平均异质性,因此我们要求$γ\geqα$。存在具有离散事件空间的复合系统的Rényi异质性的乘法分解,但在连续环境中对分解的关注较少。因此,我们描述了Rényi异质性的乘法分解,用于参数和非参数池假设下的连续混合分布。在非参数合并下,$γ$ - 近似值通常必须进行数值估算,但是乘法分解成分使得$γ\ geqα$ for $ q> 0 $。相反,在参数池中,可以有效地计算出$γ$ - 近似值,但$γ\ geqα$条件仅在$ q = 1 $时可靠地保持。我们的发现将进一步有助于连续系统中的异质性测量。

A system's heterogeneity (\textit{diversity}) is the effective size of its event space, and can be quantified using the Rényi family of indices (also known as Hill numbers in ecology or Hannah-Kay indices in economics), which are indexed by an elasticity parameter $q \geq 0$. Under these indices, the heterogeneity of a composite system (the $γ$-heterogeneity) is decomposable into heterogeneity arising from variation \textit{within} and \textit{between} component subsystems (the $α$- and $β$-heterogeneity, respectively). Since the average heterogeneity of a component subsystem should not be greater than that of the pooled system, we require that $γ\geq α$. There exists a multiplicative decomposition for Rényi heterogeneity of composite systems with discrete event spaces, but less attention has been paid to decomposition in the continuous setting. We therefore describe multiplicative decomposition of the Rényi heterogeneity for continuous mixture distributions under parametric and non-parametric pooling assumptions. Under non-parametric pooling, the $γ$-heterogeneity must often be estimated numerically, but the multiplicative decomposition holds such that $γ\geq α$ for $q > 0$. Conversely, under parametric pooling, $γ$-heterogeneity can be computed efficiently in closed-form, but the $γ\geq α$ condition holds reliably only at $q=1$. Our findings will further contribute to heterogeneity measurement in continuous systems.

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