Asymptotic normality of the local linear estimator of the functional expectile regression

IF 1.4 3区 数学 Q2 STATISTICS & PROBABILITY Journal of Multivariate Analysis Pub Date : 2023-12-05 DOI:10.1016/j.jmva.2023.105281
Ouahiba Litimein , Ali Laksaci , Larbi Ait-Hennani , Boubaker Mechab , Mustapha Rachdi
{"title":"Asymptotic normality of the local linear estimator of the functional expectile regression","authors":"Ouahiba Litimein ,&nbsp;Ali Laksaci ,&nbsp;Larbi Ait-Hennani ,&nbsp;Boubaker Mechab ,&nbsp;Mustapha Rachdi","doi":"10.1016/j.jmva.2023.105281","DOIUrl":null,"url":null,"abstract":"<div><p><span>We are concerned with the nonparametric estimation of the expectile functional regression. More precisely, we build an estimator, by the local linear smoothing approach, of the conditional expectile. Then we establish the </span>asymptotic distribution<span> of the constructed estimator. Establishing this result requires the Bahadur representation of the conditional expectile. The latter is obtained under certain standard conditions which cover the functional aspect of the data as well as the nonparametric characteristic of the model. The real impact of this result in nonparametric functional statistics has been discussed and highlighted using artificial data.</span></p></div>","PeriodicalId":16431,"journal":{"name":"Journal of Multivariate Analysis","volume":null,"pages":null},"PeriodicalIF":1.4000,"publicationDate":"2023-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Multivariate Analysis","FirstCategoryId":"100","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0047259X23001276","RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
引用次数: 0

Abstract

We are concerned with the nonparametric estimation of the expectile functional regression. More precisely, we build an estimator, by the local linear smoothing approach, of the conditional expectile. Then we establish the asymptotic distribution of the constructed estimator. Establishing this result requires the Bahadur representation of the conditional expectile. The latter is obtained under certain standard conditions which cover the functional aspect of the data as well as the nonparametric characteristic of the model. The real impact of this result in nonparametric functional statistics has been discussed and highlighted using artificial data.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
泛函期望回归局部线性估计量的渐近正态性
我们关注期望函数回归的非参数估计。更精确地说,我们用局部线性平滑方法建立了一个条件期望的估计量。然后建立了构造的估计量的渐近分布。建立这个结果需要条件谓词的Bahadur表示。后者是在一定的标准条件下获得的,这些标准条件涵盖了数据的功能方面以及模型的非参数特性。这一结果在非参数函数统计中的实际影响已经用人工数据进行了讨论和强调。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Journal of Multivariate Analysis
Journal of Multivariate Analysis 数学-统计学与概率论
CiteScore
2.40
自引率
25.00%
发文量
108
审稿时长
74 days
期刊介绍: Founded in 1971, the Journal of Multivariate Analysis (JMVA) is the central venue for the publication of new, relevant methodology and particularly innovative applications pertaining to the analysis and interpretation of multidimensional data. The journal welcomes contributions to all aspects of multivariate data analysis and modeling, including cluster analysis, discriminant analysis, factor analysis, and multidimensional continuous or discrete distribution theory. Topics of current interest include, but are not limited to, inferential aspects of Copula modeling Functional data analysis Graphical modeling High-dimensional data analysis Image analysis Multivariate extreme-value theory Sparse modeling Spatial statistics.
期刊最新文献
Covariance parameter estimation of Gaussian processes with approximated functional inputs PDE-regularised spatial quantile regression Diagnostic checking of periodic vector autoregressive time series models with dependent errors A conditional distribution function-based measure for independence and K-sample tests in multivariate data On the exact region determined by Spearman’s ρ and Blest’s measure of rank correlation ν for bivariate extreme-value copulas
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1