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Optimal allocation in balanced sampling

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  • Tillé, Yves
  • Favre, Anne-Catherine

Abstract

The development of new sampling methods allows the selection of large balanced samples. In this paper we propose a method for computing optimal inclusion probabilities for balanced samples. Next, we show that the optimal Neyman allocation is a particular case of this method.

Suggested Citation

  • Tillé, Yves & Favre, Anne-Catherine, 2005. "Optimal allocation in balanced sampling," Statistics & Probability Letters, Elsevier, vol. 74(1), pages 31-37, August.
    • Handle: RePEc:eee:stapro:v:74:y:2005:i:1:p:31-37
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    References listed on IDEAS

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    1. repec:adr:anecst:y:1991:i:23:p:06 is not listed on IDEAS
    2. Jean-Claude Deville & Yves Tille, 2004. "Efficient balanced sampling: The cube method," Biometrika, Biometrika Trust, vol. 91(4), pages 893-912, December.
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    Cited by:

    1. R. Benedetti & M. S. Andreano & F. Piersimoni, 2019. "Sample selection when a multivariate set of size measures is available," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(1), pages 1-25, March.
    2. Hasler, Caren & Tillé, Yves, 2014. "Fast balanced sampling for highly stratified population," Computational Statistics & Data Analysis, Elsevier, vol. 74(C), pages 81-94.

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