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arXiv 2103.01320math.PRmath-phmath.MP

具有遍历强度的多玩家联赛的淬火大数定律与淬火中心极限定理

Quenched law of large numbers and quenched central limit theorem for multi-player leagues with ergodic strengths

Jacopo Borga, Benedetta Cavalli

AI总结:

本文提出一个体育多玩家联赛模型,其中球队初始强度为随机变量且随时间遍历演化,并证明了关于胜利次数的淬火大数定律和淬火中心极限定理,推广了先前模型。

摘要:

我们提出并研究了一个新的竞赛模型,具体而言是体育多玩家联赛,其中球队的初始强度是独立的同分布随机变量,在联赛的不同日期根据独立的遍历过程演化。每场比赛的结果是随机的:一支球队战胜另一支球队的概率由比赛当天两队强度的函数决定。我们的模型推广了物理和数学文献中研究的一些先前模型,并由不同的参数定义,这些参数可以进行统计校准。我们证明了淬火——以球队初始强度为条件——大数定律和淬火中心极限定理,涉及球队根据其初始强度的胜利次数。为了获得我们的结果,我们证明了一个独立有趣的定理。对于满足混合条件的平稳过程 $\xi=(\xi_i)_{i\in \mathbb{N}}$ 和独立的同分布随机变量序列 $(s_i)_{i\in \mathbb{N}}$,我们证明了淬火——以 $(s_i)_{i\in\mathbb{N}}$ 为条件——中心极限定理,适用于形如 $\sum_{i=1}^{n}g\left(\xi_i,s_i\right)$ 的和,其中 $g$ 是有界可测函数。我们强调,随机变量 $g\left(\xi_i,s_i\right)$ 在以 $(s_i)_{i\in\mathbb{N}}$ 为条件时不是平稳的。

英文摘要:

We propose and study a new model for competitions, specifically sports multi-player leagues where the initial strengths of the teams are independent i.i.d. random variables that evolve during different days of the league according to independent ergodic processes. The result of each match is random: the probability that a team wins against another team is determined by a function of the strengths of the two teams in the day the match is played. Our model generalizes some previous models studied in the physical and mathematical literature and is defined in terms of different parameters that can be statistically calibrated. We prove a quenched -- conditioning on the initial strengths of the teams -- law of large numbers and a quenched central limit theorem for the number of victories of a team according to its initial strength. To obtain our results, we prove a theorem of independent interest. For a stationary process $ξ=(ξ_i)_{i\in \mathbb{N}}$ satisfying a mixing condition and an independent sequence of i.i.d. random variables $(s_i)_{i\in \mathbb{N}}$, we prove a quenched -- conditioning on $(s_i)_{i\in\mathbb{N}}$ -- central limit theorem for sums of the form $\sum_{i=1}^{n}g\left(ξ_i,s_i\right)$, where $g$ is a bounded measurable function. We highlight that the random variables $g\left(ξ_i,s_i\right)$ are not stationary conditioning on $(s_i)_{i\in\mathbb{N}}$.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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