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REP provides meaningful measurement of support across datasets

机译:REP提供跨数据集的有意义的支持度量

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摘要

The relative optimality of the best and next-best hypotheses indicates the strength of support for the optimal hypothesis and may be calculated as either the difference or ratio of their optimality scores. The Goodman-Bremer support measure (GB) calculates the support for a given clade in the most parsimonious tree as the difference between the length of the optimal tree and the optimal tree that lacks that clade. The ratio of explanatory power (REP) support measure calculates support as the ratio of optimality scores, which simplifies to the ratio of observed GB and the maximum possible GB, GB/GB_(max). In this paper we show that REP support provides a logical basis for comparison of support across datasets and that recent claims to the contrary are incorrect.
机译:最佳假设和次最佳假设的相对最优性表明了对最优假设的支持强度,可以将其作为最优分数的差或比率来计算。 Goodman-Bremer支持量度(GB)将最简约树中给定进化枝的支持度计算为最佳树的长度与缺少该进化枝的最优树的长度之差。解释能力(REP)支持度量的比率将支持计算为最佳分数的比率,这简化为观察到的GB与最大可能GB的比率GB / GB_(max)。在本文中,我们表明REP支持为跨数据集的支持比较提供了逻辑基础,而最近相反的说法是不正确的。

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