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Published in:
Missing Observations and Data Quality Improvement Read chapter Read first chapter

2013 | OriginalPaper | Chapter

2. Sampling Using Ranked Sets: Basic Concepts

Author : Carlos N. Bouza-Herrera

Published in: Handling Missing Data in Ranked Set Sampling

Publisher: Springer Berlin Heidelberg

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Abstract

Simple random sampling is the kernel of sampling theory. The basic theory of statistical inference is supported by the assumption of using samples selected by means of this design. During the last decade Ranked Set Sampling has appeared as a challenge to this design. It is implemented by selecting units with replacement and the sampled units are ordered (ranked). Each order statistic is observed once. This process can be repeated if needed to observe various realizations of each order statistic. A review of the most significant results is developed in this chapter, taking into account the modeling of missing data.

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previous chapter Missing Observations and Data Quality Improvement
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Metadata
Title
Sampling Using Ranked Sets: Basic Concepts
Author
Carlos N. Bouza-Herrera
Copyright Year
2013
Publisher
Springer Berlin Heidelberg
Book
Handling Missing Data in Ranked Set Sampling

Print ISBN: 978-3-642-39898-8

Electronic ISBN: 978-3-642-39899-5

Copyright Year: 2013

DOI
https://doi.org/10.1007/978-3-642-39899-5_2

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