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The sampling balanced by the cube method and the rejection method



ID: <http://hdl.handle.net/20.500.11794/26960>


In recent years, balanced sampling techniques have experienced a renewed interest. They allow to reproduce the structure of the population in samples in order to improve the efficiency of survey estimates. New procedures have been proposed. These include the cube method, an exact method presented by Deville and Tillé (2004), and an approximate method, the Fuller (2009) rejective algorithm. After a brief presentation of these methods as part of an angler survey, we compare using Monte Carlo simulations, the survey designs produced by these two sampling algorithms. We also use this as an opportunity to check whether these methods modify the inclusion probabilities.

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