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Conditional and restricted Pareto sampling: two new methods for unequal probability sampling
Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
2010 (English)In: Scandinavian Journal of Statistics, ISSN 0303-6898, E-ISSN 1467-9469, Vol. 37, no 3, 514-530 p.Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Wiley-Blackwell, 2010. Vol. 37, no 3, 514-530 p.
Keyword [en]
acceptance–rejection, conditioned uniform random numbers, Gibbs sampling, inclusion probability, linear programming, Pareto sampling, permanent random numbers, unequal probability sampling
National Category
Mathematics
Identifiers
URN: urn:nbn:se:umu:diva-31089DOI: 10.1111/j.1467-9469.2010.00700.xISI: 000281001100010OAI: oai:DiVA.org:umu-31089DiVA: diva2:290874
Available from: 2010-01-28 Created: 2010-01-28 Last updated: 2017-12-12Bibliographically approved

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