Asymptotics of pooling design performance

J. K. Percus, O. E. Percus, W. J. Bruno, D. C. Torney

Research output: Contribution to journalArticle

Abstract

We analyse the expected performance of various group testing, or pooling, designs. The context is that of identifying characterized clones in a large collection of clones. Here we choose as performance criterion the expected number of unresolved 'negative' clones, and we aim to minimize this quantity. Technically, long inclusion-exclusion summations are encountered which, aside from being computationally demanding, give little inkling of the qualitative effect of parametric control on the pooling strategy. We show that readily-interpreted re-summation can be performed, leading to asymptotic forms and systematic corrections. We apply our results to randomized designs, illustrating how they might be implemented for approximating combinatorial formulae.

Original languageEnglish (US)
Pages (from-to)951-964
Number of pages14
JournalJournal of Applied Probability
Volume36
Issue number4
DOIs
StatePublished - Dec 1999

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Keywords

  • Approximation techniques
  • Asymptotic analysis
  • Combinatorial designs
  • Discrete probability

ASJC Scopus subject areas

  • Statistics and Probability
  • Mathematics(all)
  • Statistics, Probability and Uncertainty

Cite this

Percus, J. K., Percus, O. E., Bruno, W. J., & Torney, D. C. (1999). Asymptotics of pooling design performance. Journal of Applied Probability, 36(4), 951-964. https://doi.org/10.1017/S0021900200017770