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arXiv 1002.0224math.PRmath.STstat.TH
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相互作用粒子系统U-统计量的收敛性

Convergence of U-statistics for interacting particle systems

P. Del Moral, F. Patras, S. Rubenthaler

摘要:

U-统计量的收敛性已被深入研究的家庭的i.i.d.的基础上估计。随机变量及其变体。在大多数情况下,独立性假设是至关重要的[Lee 90,de 99]。在处理费曼-卡茨和其他蒙特卡罗类型的相互作用粒子系统时,人们面临着一种新的问题。也就是说,在通过相应算法获得的N个粒子的样本中,粒子的分布是相关的-尽管它们中的任何有限数量相对于粒子的总数N是渐近独立的。在这篇文章中,利用粒子系统的精细渐近性,我们证明了U-统计量在这个框架下的收敛定理。

英文摘要:

The convergence of U-statistics has been intensively studied for estimators based on families of i.i.d. random variables and variants of them. In most cases, the independence assumption is crucial [Lee90, de99]. When dealing with Feynman-Kac and other interacting particle systems of Monte Carlo type, one faces a new type of problem. Namely, in a sample of N particles obtained through the corresponding algorithms, the distributions of the particles are correlated -although any finite number of them is asymptotically independent with respect to the total number N of particles. In the present article, exploiting the fine asymptotics of particle systems, we prove convergence theorems for U-statistics in this framework.

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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