On Inconsistency of the Jackknife-after-Bootstrap Bias Estimator for Dependent Data

Soumendra Nath Lahiri

Journal of Multivariate Analysis, 1997, vol. 63, issue 1, 15-34

Abstract: B. Efron introducedjackknife-after-bootstrapas a computationally efficient method for estimating standard errors of bootstrap estimators. In a recent paper consistency of the jackknife-after-bootstrap variance estimators has been established for different bootstrap quantities for independent and dependent data. In this paper, it is shown that in the dependent case, the standard jackknife-after-bootstrap estimator for the bias of block bootstrap quantities is inconsistent for almost any sensible choice of the blocking parameters. Some alternative bias estimators are proposed and shown to be consistent.

Keywords: jackknife; block; bootstrap; consistency; weak; dependence (search for similar items in EconPapers)
Date: 1997
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0047-259X(97)91699-7
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:jmvana:v:63:y:1997:i:1:p:15-34

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

Access Statistics for this article

Journal of Multivariate Analysis is currently edited by de Leeuw, J.

More articles in Journal of Multivariate Analysis from Elsevier
Bibliographic data for series maintained by Catherine Liu ().