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A fast algorithm for balanced sampling

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Summary

The cube method (Deville & Tillé 2004) is a large family of algorithms that allows selecting balanced samples with equal or unequal inclusion probabilities. In this paper, we propose a very fast implementation of the cube method. The execution time does not depend on the square of the population size anymore, but only on the population size. Balanced samples can thus be selected in very large populations of several hundreds of thousands of units.

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References

  • Bertrand, P., Christian, B., Chauvet, G. & Grosbras, J.-M. (2004), Plans de sondage pour le recensement rénové de la population, in ‘Séries INSEE Méthodes: Actes des Journées de Méthodologie Statistique’, Paris: INSEE, to appear, Paris.

    Google Scholar 

  • Deville, J.-C. & Tillé, Y. (1998), ‘Unequal probability sampling without replacement through a splitting method’, Biometrika 85, 89–101.

    Article  MathSciNet  Google Scholar 

  • Deville, J.-C. & Tillé, Y. (2004), ‘Efficient balanced sampling: the cube method’, Biometrika 91, 893–912.

    Article  MathSciNet  Google Scholar 

  • Deville, J.-C. & Tillé, Y. (2005), ‘Variance approximation under balanced sampling’, Journal of Statistical Planning and Inference 128, 411–425.

    Article  MathSciNet  Google Scholar 

  • Dumais, J. & Isnard, M. (2000), Le sondage de logements dans les grandes communes dans le cadre du recensement rénové de la population, in ‘Séries INSEE Méthodes: Actes des Journées de Méthodologie Statistique’, Vol. 100, pp. 37–76, Paris: INSEE, Paris, pp. 37–76.

    Google Scholar 

  • Royall, R. & Herson, J. (1973), ‘Robust estimation in finite populations I’, Journal of the American Statistical Association 68, 880–889.

    Article  MathSciNet  Google Scholar 

  • Scott, A., Brewer, K. & Ho, E. (1978), ‘Finite population sampling and robust estimation’, Journal of American Statistical Association 73, 359–361.

    Article  MathSciNet  Google Scholar 

  • Tillé, Y. (2001), Théorie des sondages: échantillonnage et estimation en populations finies, Dunod, Paris.

    Google Scholar 

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Acknowledgements

The authors wish to than Jean Dumais for his insightful comments that have improved the clarity of the paper.

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Authors and Affiliations

  1. Laboratoire de Statistique d’Enquête, CREST-ENSAI, rue Blaise Pascal, Campus de Ker Lann, 35170, Bruz, France

    Guillaume Chauvet

  2. Statistics Group, University of Neuchâtel, Espace de l’Europe 4, Case postale 827, 2002, Neuchtel, Switzerland

    Yves Tillé

Authors
  1. Guillaume Chauvet
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  2. Yves Tillé
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Appendix

Appendix

Algorithm 1
figure Alg1

General balanced procedure: flight phase

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Algorithm 2
figure Alg2

Fast algorithm for the flight phase

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Algorithm 3
figure Alg3

Pivotal method for unequal inclusion probabilities

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Chauvet, G., Tillé, Y. A fast algorithm for balanced sampling. Computational Statistics 21, 53–62 (2006). https://doi.org/10.1007/s00180-006-0250-2

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  • DOI: https://doi.org/10.1007/s00180-006-0250-2

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