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Nonparametric predictive subset selection for proportions

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  • Coolen, F.P.A.
  • Coolen-Schrijner, P.

Abstract

We present nonparametric predictive lower and upper probabilities for comparison of future numbers of successes in Bernoulli trials, for k[greater-or-equal, slanted]2 independent groups, using proportions data per group. We consider lower and upper probabilities related to subsets of the k groups, both for the event that the selected subset contains the group which gives the highest number of successes in m future trials for each group, and the event that all groups in the selected subset give more successes in m future trials than all not selected groups.

Suggested Citation

  • Coolen, F.P.A. & Coolen-Schrijner, P., 2006. "Nonparametric predictive subset selection for proportions," Statistics & Probability Letters, Elsevier, vol. 76(15), pages 1675-1684, September.
    • Handle: RePEc:eee:stapro:v:76:y:2006:i:15:p:1675-1684
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    References listed on IDEAS

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    1. Coolen, F. P. A., 1996. "Comparing two populations based on low stochastic structure assumptions," Statistics & Probability Letters, Elsevier, vol. 29(4), pages 297-305, September.
    2. David J. Spiegelhalter & Paul Aylin & Nicola G. Best & Stephen J. W. Evans & Gordon D. Murray, 2002. "Commissioned analysis of surgical performance using routine data: lessons from the Bristol inquiry," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 165(2), pages 191-221, June.
    3. J. F. Lawless & Marc Fredette, 2005. "Frequentist prediction intervals and predictive distributions," Biometrika, Biometrika Trust, vol. 92(3), pages 529-542, September.
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    1. P Coolen-Schrijner & F. P. A. Coolen, 2007. "Non-parametric predictive comparison of success-failure data in reliability," Journal of Risk and Reliability, , vol. 221(4), pages 319-327, December.
    2. Stojaković, Mila, 2012. "Set valued probability and its connection with set valued measure," Statistics & Probability Letters, Elsevier, vol. 82(6), pages 1043-1048.

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