Open Access
Translator Disclaimer
2021 Asymptotic validity of bootstrap confidence intervals in nonparametric regression without an additive model
Liang Wang, Dimitris N. Politis
Electron. J. Statist. 15(1): 392-426 (2021). DOI: 10.1214/20-EJS1781

Abstract

Bootstrap for nonparametric regression has been around for more than 30 years. Nevertheless, most results are based on assuming an additive regression model with respect to independent and identical (i.i.d.) errors. An exception is the Local Bootstrap of Shi [23] for which, however, no bootstrap consistency results are available. We attempt to remedy this here while at the same time showing bootstrap consistency for a more general class of methods that fall under the heading of Model-free Bootstrap of Politis [18].

Citation

Download Citation

Liang Wang. Dimitris N. Politis. "Asymptotic validity of bootstrap confidence intervals in nonparametric regression without an additive model." Electron. J. Statist. 15 (1) 392 - 426, 2021. https://doi.org/10.1214/20-EJS1781

Information

Received: 1 May 2019; Published: 2021
First available in Project Euclid: 6 January 2021

Digital Object Identifier: 10.1214/20-EJS1781

JOURNAL ARTICLE
35 PAGES


SHARE
Vol.15 • No. 1 • 2021
Back to Top