Asymptotic distribution of the wavelet-based estimators of multivariate regression functions under weak dependence

IF 16.4 1区化学 Q1 CHEMISTRY, MULTIDISCIPLINARY

Accounts of Chemical Research Pub Date : 2023-01-01 DOI:10.7153/jmi-2023-17-32

Soumaya Allaoui, S. Bouzebda, Jich ng Liu

引用次数: 1

Abstract

. This paper investigates the nonparametric linear wavelet-based estimators of multi-variate regression functions. Under mild conditions, we establish the asymptotic normality under the weak dependence, which incorporates mixing and association concepts. This framework applies to numerous classes of intriguing statistical processes, primarily Gaussian sequences and, more generally, Bernoulli shifts. We give an application for the con ﬁ dence interval.

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弱相关条件下多元回归函数小波估计的渐近分布

．研究了多变量回归函数的非参数线性小波估计。在温和条件下，我们建立了弱依赖下的渐近正态性，其中包含了混合和关联的概念。这个框架适用于许多有趣的统计过程，主要是高斯序列，更普遍的是伯努利位移。给出了置信区间的一个应用。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Accounts of Chemical Research 化学-化学综合

CiteScore

31.40

自引率

1.10%

发文量

312

审稿时长

2 months

期刊介绍： Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.