{"title":"Self-Normalized Moderate Deviations for Degenerate <i>U</i>-Statistics.","authors":"Lin Ge, Hailin Sang, Qi-Man Shao","doi":"10.3390/e27010041","DOIUrl":null,"url":null,"abstract":"<p><p>In this paper, we study self-normalized moderate deviations for degenerate <i>U</i>-statistics of order 2. Let {Xi,i≥1} be i.i.d. random variables and consider symmetric and degenerate kernel functions in the form h(x,y)=∑l=1∞λlgl(x)gl(y), where λl>0, Egl(X1)=0, and gl(X1) is in the domain of attraction of a normal law for all l≥1. Under the condition ∑l=1∞λl<∞ and some truncated conditions for {gl(X1):l≥1}, we show that logP(∑1≤i≠j≤nh(Xi,Xj)max1≤l<∞λlVn,l2≥xn2)∼-xn22 for xn→∞ and xn=o(n), where Vn,l2=∑i=1ngl2(Xi). As application, a law of the iterated logarithm is also obtained.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 1","pages":""},"PeriodicalIF":2.1000,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11765170/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Entropy","FirstCategoryId":"101","ListUrlMain":"https://doi.org/10.3390/e27010041","RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"PHYSICS, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, we study self-normalized moderate deviations for degenerate U-statistics of order 2. Let {Xi,i≥1} be i.i.d. random variables and consider symmetric and degenerate kernel functions in the form h(x,y)=∑l=1∞λlgl(x)gl(y), where λl>0, Egl(X1)=0, and gl(X1) is in the domain of attraction of a normal law for all l≥1. Under the condition ∑l=1∞λl<∞ and some truncated conditions for {gl(X1):l≥1}, we show that logP(∑1≤i≠j≤nh(Xi,Xj)max1≤l<∞λlVn,l2≥xn2)∼-xn22 for xn→∞ and xn=o(n), where Vn,l2=∑i=1ngl2(Xi). As application, a law of the iterated logarithm is also obtained.
期刊介绍:
Entropy (ISSN 1099-4300), an international and interdisciplinary journal of entropy and information studies, publishes reviews, regular research papers and short notes. Our aim is to encourage scientists to publish as much as possible their theoretical and experimental details. There is no restriction on the length of the papers. If there are computation and the experiment, the details must be provided so that the results can be reproduced.