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Handling Missing Data in Ranked Set Sampling

By Carlos N. Bouza-Herrera

part of the SpringerBriefs in Statistics series

Handling Missing Data in Ranked Set Sampling by Carlos N. Bouza-Herrera
About Handling Missing Data in Ranked Set Sampling

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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  • Language:
  • English
  • ISBN:
  • 9783642398988
  • Binding:
  • Paperback
  • Pages:
  • 116
  • Published:
  • October 14, 2013
  • Edition:
  • 2013
  • Dimensions:
  • 155x235x7 mm.
  • Weight:
  • 2058 g.
Delivery: 1-2 weeks
Expected delivery: December 5, 2024

About Carlos N. Bouza-Herrera

View all books by Carlos N. Bouza-Herrera

Description of Handling Missing Data in Ranked Set Sampling

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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