Nearest neighbors estimation for long memory functional data

Lihong Wang

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Nearest neighbors estimation for long memory functional data

机译：最近的邻居估计长内存功能数据

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摘要

In this paper, we consider the asymptotic properties of the nearest neighbors estimation for long memory functional data. Under some regularity assumptions, we investigate the asymptotic normality and the uniform consistency of the nearest neighbors estimators for the nonparametric regression models when the explanatory variable and the errors are of long memory and the explanatory variable takes values in some abstract functional space. The finite sample performance of the proposed estimator is discussed through simulation studies.

机译：在本文中，我们考虑了最近邻居估计的长记忆功能数据的渐近特性。在一些规律性假设下，我们调查渐近常态以及当解释变量和误差是长存储器的非参数回归模型的渐近常态和均匀一致性，并且解释变量在一些抽象功能空间中取得值。通过模拟研究讨论了所提出的估计器的有限样本性能。

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来源
《Statistical Methods and Applications》 |2020年第4期|709-725|共17页
作者
Lihong Wang;
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作者单位

Department of Mathematics Nanjing University Nanjing 210093 People's Republic of China;

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正文语种 eng
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关键词
Asymptotic normality; Functional data; Long memory; Nearest neighbors estimation; Uniform consistency;

机译：渐近常态;功能数据;漫长记忆;最近的邻居估计;统一一致;

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Nearest neighbors estimation for long memory functional data

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