论文标题
网络HHD:量化比赛特征模型中的循环竞争
The Network HHD: Quantifying Cyclic Competition in Trait-Performance Models of Tournaments
论文作者
论文摘要
竞争性比赛出现在体育,政治,人口生态学和动物行为中。所有这些领域都开发了对竞争对手进行评估和对其进行排名的方法。如果比赛与任何排名不一致,则比赛是不及物的。不及事的比赛中包含岩纸剪裁类型的周期。离散的Helmholtz-Hodge分解(HHD)非常适合描述不及物的比赛。它将锦标赛分为完美及其完美的循环组件,其中完美的传递组件与一组评级相关联。循环分量的大小可以用作衡量不强制性的量度。在这里,我们表明HHD自然来自具有简单统计解释的两类锦标赛。然后,我们讨论定义等效分解的六组不同的假设。该分析促使选择使用HHD和其他现有方法。竞争的成功通常是由竞争对手的特征介导的。一个特质的绩效模型假设一个竞争者击败另一个竞争者的概率可以作为其特征的函数表示。我们表明,如果每个竞争对手的特征是从性状分布中独立且相同绘制的,则可以明确计算网络中预期的不强制性程度。使用此结果,我们表明,可以增加可以竞争的竞争对手的成对数量促进循环竞争,并增加$ a $ a $ a $ a $ a $ a $ a $ a $ a $ a $ a $ a $ a $ a $ c $ a $ c $ a $ c $ a $ c $ a $ c $ c $ a $ c $ c $ a $ c $ c $相关性。因此,可以通过分析这种相关性来理解环状竞争的预期大小。提供了一个说明性示例。
Competitive tournaments appear in sports, politics, population ecology, and animal behavior. All of these fields have developed methods for rating competitors and ranking them accordingly. A tournament is intransitive if it is not consistent with any ranking. Intransitive tournaments contain rock-paper-scissor type cycles. The discrete Helmholtz-Hodge decomposition (HHD) is well adapted to describing intransitive tournaments. It separates a tournament into perfectly transitive and perfectly cyclic components, where the perfectly transitive component is associated with a set of ratings. The size of the cyclic component can be used as a measure of intransitivity. Here we show that the HHD arises naturally from two classes of tournaments with simple statistical interpretations. We then discuss six different sets of assumptions that define equivalent decompositions. This analysis motivates the choice to use the HHD among other existing methods. Success in competition is typically mediated by the traits of the competitors. A trait-performance model assumes that the probability that one competitor beats another can be expressed as a function of their traits. We show that, if the traits of each competitor are drawn independently and identically from a trait distribution then the expected degree of intransitivity in the network can be computed explicitly. Using this result we show that increasing the number of pairs of competitors who could compete promotes cyclic competition, and that increasing the correlation in the performance of $A$ against $B$ with the performance of $A$ against $C$ promotes transitive competition. The expected size of cyclic competition can thus be understood by analyzing this correlation. An illustrative example is provided.