Large Deviation Principle for Moderate Deviation Probabilities of Bootstrap Empirical Measures

被引:0
|
作者
Ermakov M.S. [1 ]
机构
[1] Mechanical Engineering Problems Institute of RAS, St. Petersburg State University, St. Petersburg
关键词
Probability Measure; Moderate Deviation; Empirical Measure; Empirical Process; Large Deviation Principle;
D O I
10.1007/s10958-014-2189-0
中图分类号
学科分类号
摘要
We prove two Large Deviation Principles (LDP) in the zone of moderate deviation probabilities. First we establish the LDP for conditional distributions of moderate deviations of empirical bootstrap measures given an empirical probability measure. Then we establish the LDP for the joint distributions of an empirical measure and a bootstrap empirical measure. Using these LDPs, similar LDPs for differentiable statistical functionals can be established. The LDPs for moderate deviations of an empirical quantile process and an empirical bootstrap copula function are provided as illustrations of these results. Bibliography: 28 titles. © 2014, Springer Science+Business Media New York.
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页码:90 / 115
页数:25
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