Handling Missing Data in Ranked Set Sampling

Name: Handling Missing Data in Ranked Set Sampling
Author: Carlos N. Bouza-Herrera

Carlos N. Bouza-Herrera

Springer-Verlag Berlin and Heidelberg GmbH & Co. KG

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?The existence of missing observations is a very important aspect to be considered in the application of survey sampling, for example. Traditionally, simple random sampling is used to select samples. RSS models are developed as counterparts of well-known simple random sampling (SRS) models.

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