Using i.i.d. bootstrap inference for general non-i.i.d. models

Regina Y. Liu; Kesar Singh

doi:https://doi.org/10.1016/0378-3758(94)00008-J

Using i.i.d. bootstrap inference for general non-i.i.d. models

Regina Y. Liu, Kesar Singh

School of Arts and Sciences, Statistics

Rutgers, The State University

Research output: Contribution to journal › Article › peer-review

16 Scopus citations

Abstract

It is observed here that bootstrap confidence intervals constructed under i.i.d. assumptions turn out to be 'conservative' under non-i.i.d. models, and thus they can be regarded as fall-back devices in the non-i.i.d. situations where exact inference is not available.

Original language	American English
Pages (from-to)	67-75
Number of pages	9
Journal	Journal of Statistical Planning and Inference
Volume	43
Issue number	1-2
DOIs	https://doi.org/10.1016/0378-3758(94)00008-J
State	Published - Jan 1995

ASJC Scopus subject areas

Statistics and Probability
Statistics, Probability and Uncertainty
Applied Mathematics

Keywords

62G15
Bootstrap confidence intervals
Conservative inference
Coverage probability
Jackknife procedures
Product-limit estimator

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Cite this

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title = "Using i.i.d. bootstrap inference for general non-i.i.d. models",

abstract = "It is observed here that bootstrap confidence intervals constructed under i.i.d. assumptions turn out to be 'conservative' under non-i.i.d. models, and thus they can be regarded as fall-back devices in the non-i.i.d. situations where exact inference is not available.",

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AU - Liu, Regina Y.

AU - Singh, Kesar

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AB - It is observed here that bootstrap confidence intervals constructed under i.i.d. assumptions turn out to be 'conservative' under non-i.i.d. models, and thus they can be regarded as fall-back devices in the non-i.i.d. situations where exact inference is not available.

KW - 62G15

KW - Bootstrap confidence intervals

KW - Conservative inference

KW - Coverage probability

KW - Jackknife procedures

KW - Product-limit estimator

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ER -

Using i.i.d. bootstrap inference for general non-i.i.d. models

Abstract

ASJC Scopus subject areas

Keywords

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