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Conditional and Restricted Pareto Sampling: Two New Methods for Unequal Probability Sampling



Two new unequal probability sampling methods are introduced: conditional and restricted Pareto sampling. The advantage of conditional Pareto sampling compared with standard Pareto sampling, introduced by Rosén ("J. Statist. Plann. Inference", 62, 1997, 135, 159), is that the factual inclusion probabilities better agree with the desired ones. Restricted Pareto sampling, preferably conditioned or adjusted, is able to handle cases where there are several restrictions on the sample and is an alternative to the recent cube method for balanced sampling introduced by Deville and Tillé ("Biometrika", 91, 2004, 893). The new sampling designs have high entropy and the involved random numbers can be seen as permanent random numbers. Copyright (c) 2010 Board of the Foundation of the Scandinavian Journal of Statistics.

DOI identifier: 10.1111/j.1467-9469.2010.00700.x
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