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arXiv 0904.1950math.PRmath.STstat.TH
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独立随机函数和范数的一致界

Uniform bounds for norms of sums of independent random functions

Alexander Goldenshluger, Oleg Lepski

摘要:

在本文中,我们开发了一个通用的机器,寻找显式一致的概率和矩界的次可加正泛函的随机过程。使用开发的一般技术,我们推导出统一的${\mathbb{L}}_s$规范的经验和回归型过程的界限。通过应用于核密度估计和回归函数的非参数估计过程,说明了所得结果的正确性。

英文摘要:

In this paper, we develop a general machinery for finding explicit uniform probability and moment bounds on sub-additive positive functionals of random processes. Using the developed general technique, we derive uniform bounds on the ${\mathbb{L}}_s$-norms of empirical and regression-type processes. Usefulness of the obtained results is illustrated by application to the processes appearing in kernel density estimation and in nonparametric estimation of regression functions.

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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