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Statistics for Exceptional Athletics Records

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  • Michael E. Robinson
  • Jonathan A. Tawn

Abstract

Extreme records in athletics are increasingly questioned as being due to the use of performance enhancing drugs. to assess such performances, statistical methods are developed that are based on extreme value techniques for estimating the ultimate performance possible by the current population of competing athletes. These methods are applied to the analysis of data from the women's 3000 m track event, where we find that a recently broken record shows signs of being inconsistent with previous performances.

Suggested Citation

  • Michael E. Robinson & Jonathan A. Tawn, 1995. "Statistics for Exceptional Athletics Records," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 44(4), pages 499-511, December.
    • Handle: RePEc:bla:jorssc:v:44:y:1995:i:4:p:499-511
    DOI: 10.2307/2986141
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    Cited by:

    1. Harry Spearing & Jonathan Tawn & David Irons & Tim Paulden & Grace Bennett, 2021. "Ranking, and other properties, of elite swimmers using extreme value theory," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(1), pages 368-395, January.
    2. Francesco Pauli & Stuart Coles, 2001. "Penalized likelihood inference in extreme value analyses," Journal of Applied Statistics, Taylor & Francis Journals, vol. 28(5), pages 547-560.
    3. Einmahl, John H. J. & Magnus, Jan R., 2008. "Records in Athletics Through Extreme-Value Theory," Journal of the American Statistical Association, American Statistical Association, vol. 103(484), pages 1382-1391.
    4. A.B. Schmiedt & H.H. Dickert & W. Bleck & U. Kamps, 2014. "Multivariate extreme value analysis and its relevance in a metallographical application," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(3), pages 582-595, March.
    5. Wang, Bing Xing & Yu, Keming & Coolen, Frank P.A., 2015. "Interval estimation for proportional reversed hazard family based on lower record values," Statistics & Probability Letters, Elsevier, vol. 98(C), pages 115-122.
    6. Eric T. Bradlow & Young-Hoon Park, 2007. "Bayesian Estimation of Bid Sequences in Internet Auctions Using a Generalized Record-Breaking Model," Marketing Science, INFORMS, vol. 26(2), pages 218-229, 03-04.

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