Nonparametric Recursive Method for Generalized Kernel Estimators for Dependent Functional Data

被引：0

作者：

Yousri Slaoui

机构：

[1] Univ. Poitiers,

[2] Lab. Math. et Appl.,undefined

来源：

Sankhya A | 2024年 / 86卷

关键词：

Regression estimation; dependent functional data; stochastic approximation algorithm; Primary 62G08; 62L20; 62G09; Secondary 65D10;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

In the present paper, we are concerned with a generalized kernel estimators defined by the stochastic approximation algorithm in the case of dependent functional data. We establish the central limit theorem for the proposed estimators under some mild conditions. We then approach the distribution of the bias distribution of our estimate by the bootstrapped distribution when it is conditioned by the data using the Kolmogorov distance.

引用

页码：392 / 430

页数：38

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