一维经验测度,序统计量和坎托罗维奇输运距离

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2019-09-01 DOI:10.1090/memo/1259
S. Bobkov, M. Ledoux
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引用次数: 221

摘要

本文研究了在Kantorovich输运距离Wp中,独立同分布实值随机变量k≥1的样本(Xk)上,经验测度μn =1 n∑n k=1 δXk, n≥1的收敛速度。重点讨论了期望值Kantorovich距离E(Wp(μn, μ))或[E(Wp p(μn, μ))]1/p在测度μ及其分布函数上的矩和解析条件下的有限范围边界。该研究描述了各种速率,从标准的1√n到较慢的速率,以及在各种情况下固定n时E(Wp(μn, μ))的下界和上界。序统计量、均匀样本约简、beta分布分析、逆分布函数、对数凹性是研究的主要工具。两个详细的附录收集了关于反分布函数和beta分布及其密度的经典事实和一些新的事实。
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One-dimensional empirical measures, order statistics, and Kantorovich transport distances
This work is devoted to the study of rates of convergence of the empirical measures μn = 1 n ∑n k=1 δXk , n ≥ 1, over a sample (Xk)k≥1 of independent identically distributed real-valued random variables towards the common distribution μ in Kantorovich transport distances Wp. The focus is on finite range bounds on the expected Kantorovich distances E(Wp(μn, μ)) or [ E(W p p (μn, μ)) ]1/p in terms of moments and analytic conditions on the measure μ and its distribution function. The study describes a variety of rates, from the standard one 1 √ n to slower rates, and both lower and upperbounds on E(Wp(μn, μ)) for fixed n in various instances. Order statistics, reduction to uniform samples and analysis of beta distributions, inverse distribution functions, logconcavity are main tools in the investigation. Two detailed appendices collect classical and some new facts on inverse distribution functions and beta distributions and their densities necessary to the investigation.
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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