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A general exact optimal sample allocation algorithm: With bounded cost and bounded sample sizes

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  • Wright, Tommy

Abstract

With a bound on cost and bounds on stratum sample sizes, a cost weighted objective function is decomposed to reveal a general simple exact optimal sample allocation algorithm for minimizing sampling variances. Some known allocation methods are special cases.

Suggested Citation

  • Wright, Tommy, 2020. "A general exact optimal sample allocation algorithm: With bounded cost and bounded sample sizes," Statistics & Probability Letters, Elsevier, vol. 165(C).
    • Handle: RePEc:eee:stapro:v:165:y:2020:i:c:s0167715220301322
    DOI: 10.1016/j.spl.2020.108829
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    References listed on IDEAS

    as
    1. Wright, Tommy, 2017. "Exact optimal sample allocation: More efficient than Neyman," Statistics & Probability Letters, Elsevier, vol. 129(C), pages 50-57.
    2. Tommy Wright, 2012. "The Equivalence of Neyman Optimum Allocation for Sampling and Equal Proportions for Apportioning the U.S. House of Representatives," The American Statistician, Taylor & Francis Journals, vol. 66(4), pages 217-224, November.
    Full references (including those not matched with items on IDEAS)

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