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On the Resampling of the Unbalanced Ranked Set Sample
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Mathematics, Mathematical Statistics.
(English)Manuscript (preprint) (Other academic)
Abstract [en]

This paper considers the bootstrap approach of the unbalanced Ranked Set Sampling (RSS) method. Herethe sequence bootstrap is used to shift the analysis of the unbalanced RSS method to an analysis ofthe balanced RSS sample, and balanced RSS is also discussed. Here the consequences of differentalgorithms for carrying out resampling are discussed. The pro­posed methods are studied using Monte Carloinvestigations. Furthermore, the theoretical approach is discussed.

Keyword [en]
Bootstrap method; Monte Carlo simulation; Ranked set sample
National Category
Probability Theory and Statistics
Research subject
Statistics
Identifiers
URN: urn:nbn:se:uu:diva-158983OAI: oai:DiVA.org:uu-158983DiVA: diva2:441935
Available from: 2011-09-19 Created: 2011-09-19 Last updated: 2012-02-16

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