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

IF 1.1 3区 数学 Q1 MATHEMATICS
Soumaya Allaoui, S. Bouzebda, Jich ng Liu
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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.
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。
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来源期刊
Journal of Mathematical Inequalities
Journal of Mathematical Inequalities MATHEMATICS, APPLIED-MATHEMATICS
CiteScore
2.90
自引率
3.40%
发文量
56
审稿时长
6-12 weeks
期刊介绍: The ''Journal of Mathematical Inequalities'' (''JMI'') presents carefully selected original research articles from all areas of pure and applied mathematics, provided they are concerned with mathematical inequalities and their numerous applications. ''JMI'' will also periodically publish invited survey articles and short notes with interesting results treating the theory of inequalities, as well as relevant book reviews. Only articles written in the English language and in a lucid, expository style will be considered for publication. ''JMI'' primary audience are pure mathematicians, applied mathemathicians and numerical analysts. ''JMI'' is published quarterly; in March, June, September, and December.
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