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Title: Bootstrap method for central and intermediate order statistics under power normalization (English)
Author: Barakat, H. M.
Author: Nigm, E. M.
Author: Khaled, O. M.
Language: English
Journal: Kybernetika
ISSN: 0023-5954 (print)
ISSN: 1805-949X (online)
Volume: 51
Issue: 6
Year: 2015
Pages: 923-932
Summary lang: English
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Category: math
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Summary: It has been known for a long time that for bootstrapping the distribution of the extremes under the traditional linear normalization of a sample consistently, the bootstrap sample size needs to be of smaller order than the original sample size. In this paper, we show that the same is true if we use the bootstrap for estimating a central, or an intermediate quantile under power normalization. A simulation study illustrates and corroborates theoretical results. (English)
Keyword: bootstrap technique
Keyword: power normalization
Keyword: weak consistency
Keyword: central order statistics
Keyword: intermediate order statistics
MSC: 62F40
MSC: 62G32
idZBL: Zbl 06537788
idMR: MR3453678
DOI: 10.14736/kyb-2015-6-0923
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Date available: 2016-01-21T18:14:19Z
Last updated: 2018-01-10
Stable URL: http://hdl.handle.net/10338.dmlcz/144817
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