Hölder空间中的Bernstein-Kantorovich不变性原理与加权扫描统计量

IF 0.6 4区 数学 Q4 STATISTICS & PROBABILITY Esaim-Probability and Statistics Pub Date : 2020-01-01 DOI:10.1051/ps/2019027
A. Račkauskas, Charles Suquet
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引用次数: 4

摘要

Bernstein-Kantorovich定理陈述了E|X1|max(2,r)的有限性与n−1∕2ξn在C[0, 1]中的联合弱收敛与E∥n−1/2ξn∥∞r到E∥W∥∞r的矩收敛之间的等价性。对于0 < α < 1∕2,p(α) =(1∕2 - α) -1,证明了可分Hölder空间中n−1∕2ξn到W的Hαo与E∥n−1∕2ξn∥αr到E∥W∥αr的联合收敛当且仅当当r < p(α)时p(|X1| > t) = o(t−p(α))或当r≥p(α)时E|X1|r <∞时成立。作为一个应用,我们证明了对于每一个α < 1∕2,多边形均匀分位数过程的所有α-Hölderian弯矩收敛于布朗桥的相应弯矩。当E|X1|p <∞时,当α的自然边界为1∕2−1∕p时,我们也得到了一些α-Hölderian加权扫描统计量的n阶矩的渐近性质。
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On Bernstein–Kantorovich invariance principle in Hölder spaces and weighted scan statistics
Let ξn be the polygonal line partial sums process built on i.i.d. centered random variables Xi, i ≥ 1. The Bernstein-Kantorovich theorem states the equivalence between the finiteness of E|X1|max(2,r) and the joint weak convergence in C[0, 1] of n−1∕2ξn to a Brownian motion W with the moments convergence of E∥n−1/2ξn∥∞r to E∥W∥∞r. For 0 < α < 1∕2 and p (α) = (1 ∕ 2 - α) -1, we prove that the joint convergence in the separable Hölder space Hαo of n−1∕2ξn to W jointly with the one of E∥n−1∕2ξn∥αr to E∥W∥αr holds if and only if P(|X1| > t) = o(t−p(α)) when r < p(α) or E|X1|r < ∞ when r ≥ p(α). As an application we show that for every α < 1∕2, all the α-Hölderian moments of the polygonal uniform quantile process converge to the corresponding ones of a Brownian bridge. We also obtain the asymptotic behavior of the rth moments of some α-Hölderian weighted scan statistics where the natural border for α is 1∕2 − 1∕p when E|X1|p < ∞. In the case where the Xi’s are p regularly varying, we can complete these results for α > 1∕2 − 1∕p with an appropriate normalization.
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来源期刊
Esaim-Probability and Statistics
Esaim-Probability and Statistics STATISTICS & PROBABILITY-
CiteScore
1.00
自引率
0.00%
发文量
14
审稿时长
>12 weeks
期刊介绍: The journal publishes original research and survey papers in the area of Probability and Statistics. It covers theoretical and practical aspects, in any field of these domains. Of particular interest are methodological developments with application in other scientific areas, for example Biology and Genetics, Information Theory, Finance, Bioinformatics, Random structures and Random graphs, Econometrics, Physics. Long papers are very welcome. Indeed, we intend to develop the journal in the direction of applications and to open it to various fields where random mathematical modelling is important. In particular we will call (survey) papers in these areas, in order to make the random community aware of important problems of both theoretical and practical interest. We all know that many recent fascinating developments in Probability and Statistics are coming from "the outside" and we think that ESAIM: P&S should be a good entry point for such exchanges. Of course this does not mean that the journal will be only devoted to practical aspects.
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