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On Functional Records and Champions

Author

Listed:
  • Clément Dombry

    (Université de Franche-Comté)

  • Michael Falk

    (Institute of Mathematics)

  • Maximilian Zott

    (Institute of Mathematics)

Abstract

A record among a sequence of iid random variables $$X_1,X_2,\dots $$ X 1 , X 2 , ⋯ on the real line is defined as a member $$X_n$$ X n such that $$X_n>\max (X_1,\cdots ,X_{n-1})$$ X n > max ( X 1 , ⋯ , X n - 1 ) . Trying to generalize this concept to random vectors, or even stochastic processes with continuous sample paths, we introduce two different concepts: A simple record is a stochastic process (or a random vector) $${\varvec{X}}_n$$ X n that is larger than $${\varvec{X}}_1,\cdots ,{\varvec{X}}_{n-1}$$ X 1 , ⋯ , X n - 1 in at least one component, whereas a complete record has to be larger than its predecessors in all components. In particular, the probability that a stochastic process $${\varvec{X}}_n$$ X n is a record as n tends to infinity is studied, assuming that the processes are in the max-domain of attraction of a max-stable process. Furthermore, the conditional distribution of $${\varvec{X}}_n$$ X n given that $${\varvec{X}}_n$$ X n is a record is derived.

Suggested Citation

  • Clément Dombry & Michael Falk & Maximilian Zott, 2019. "On Functional Records and Champions," Journal of Theoretical Probability, Springer, vol. 32(3), pages 1252-1277, September.
  • Handle: RePEc:spr:jotpro:v:32:y:2019:i:3:d:10.1007_s10959-018-0811-7
    DOI: 10.1007/s10959-018-0811-7
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    References listed on IDEAS

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    1. Rafael Schmidt & Ulrich Stadtmüller, 2006. "Non‐parametric Estimation of Tail Dependence," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 33(2), pages 307-335, June.
    2. Hashorva, Enkelejd & Hüsler, Jürg, 2005. "Multiple maxima in multivariate samples," Statistics & Probability Letters, Elsevier, vol. 75(1), pages 11-17, November.
    3. de Haan, Laurens & Neves, Cláudia & Peng, Liang, 2008. "Parametric tail copula estimation and model testing," Journal of Multivariate Analysis, Elsevier, vol. 99(6), pages 1260-1275, July.
    4. Gnedin, Alexander V., 1998. "Records from a multivariate normal sample," Statistics & Probability Letters, Elsevier, vol. 39(1), pages 11-15, July.
    5. Goldie, Charles M. & Resnick, Sidney I., 1995. "Many multivariate records," Stochastic Processes and their Applications, Elsevier, vol. 59(2), pages 185-216, October.
    6. Vervaat, Wim, 1973. "Limit theorems for records from discrete distributions," Stochastic Processes and their Applications, Elsevier, vol. 1(4), pages 317-334, October.
    7. Gnedin, A. V., 1993. "On Multivariate Extremal Processes," Journal of Multivariate Analysis, Elsevier, vol. 46(2), pages 207-213, August.
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