A bootstrap functional central limit theorem for time-varying linear processes

被引：0

作者：

Beering, Carina ^{[1
,3
]}

Leucht, Anne ^{[2
]}

机构：

[1] Univ Bundeswehr Hamburg, Helmut Schmidt Univ, Res Grp Math & Stat, Hamburg, Germany

[2] Otto Friedrich Univ Bamberg, Inst Stat, Bamberg, Germany

[3] Univ Bundeswehr Hamburg, Helmut Schmidt Univ, Res Grp Math & Stat, Holstenhofweg 85, D-22043 Hamburg, Germany

来源：

JOURNAL OF NONPARAMETRIC STATISTICS | 2024年 / 36卷 / 01期

关键词：

Bootstrap; functional central limit theorem; linear process; local stationaritys; BLOCKWISE BOOTSTRAP; EMPIRICAL PROCESSES; STATIONARY; INFERENCE;

D O I：

10.1080/10485252.2023.2284896

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

We provide a functional central limit theorem for a broad class of smooth functions for possibly non-causal multivariate linear processes with time-varying coefficients. Since the limiting processes depend on unknown quantities, we propose a local block bootstrap procedure to circumvent this inconvenience in practical applications. In particular, we prove bootstrap validity for a very large class of processes. Our results are illustrated by some numerical examples.

引用

页码：240 / 263

页数：24

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