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. In human populations they may be caused by a refusal of some interviewees to give the true value for the variable of inte
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Carlos N. Bouza-Herrera
Handling Missing Data in Ranked Set Sampling
123
SpringerBriefs in Statistics
For further volumes: http://www.springer.com/series/8921
Carlos N. Bouza-Herrera
Handling Missing Data in Ranked Set Sampling
123
Carlos N. Bouza-Herrera Facultad de Matemática y Computación Universidad de La Habana Havana Cuba
ISSN 2191-544X ISBN 978-3-642-39898-8 DOI 10.1007/978-3-642-39899-5
ISSN 2191-5458 (electronic) ISBN 978-3-642-39899-5 (eBook)
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Preface
Usage is the best language teacher. Quintilianus The use of random sampling sustains the development of current statistical theory. In many cases it is necessary to have some control of the units to be selected. The solution in classic sampling is to use stratification, clustering, unequal probabilities of selection, etc. Ranked Set Sampling (RSS) is a new method of selection of samples.
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