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Handling Missing Data in Ranked Set Sampling pp 7–30Cite as

Sampling Using Ranked Sets: Basic Concepts

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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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Authors and Affiliations

  1. Facultad de Matemática y, Computaciòn, Universidad de La Habana, San Lázaro y L., Havana, 10400, Cuba

    Carlos N. Bouza-Herrera

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  1. Carlos N. Bouza-Herrera
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Correspondence to Carlos N. Bouza-Herrera .

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Bouza-Herrera, C.N. (2013). Sampling Using Ranked Sets: Basic Concepts. In: Handling Missing Data in Ranked Set Sampling. SpringerBriefs in Statistics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39899-5_2

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