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This content will become publicly available on December 22, 2016

Title: Scaling exponents for ordered maxima

We study extreme value statistics of multiple sequences of random variables. For each sequence with N variables, independently drawn from the same distribution, the running maximum is defined as the largest variable to date. We compare the running maxima of m independent sequences and investigate the probability SN that the maxima are perfectly ordered, that is, the running maximum of the first sequence is always larger than that of the second sequence, which is always larger than the running maximum of the third sequence, and so on. The probability SN is universal: it does not depend on the distribution from which the random variables are drawn. For two sequences, SN~N–1/2, and in general, the decay is algebraic, SN~N–σm, for large N. We analytically obtain the exponent σ3≅1.302931 as root of a transcendental equation. Moreover, the exponents σm grow with m, and we show that σm~m for large m.
 [1] ;  [2] ;  [1]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  2. Boston Univ., Boston, MA (United States); Univ. Paris-Saclay, Gif-sur-Yvette (France)
Publication Date:
OSTI Identifier:
Report Number(s):
Journal ID: ISSN 1539-3755; PLEEE8
Grant/Contract Number:
Accepted Manuscript
Journal Name:
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics (Print)
Additional Journal Information:
Journal Name: Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics (Print); Journal Volume: 92; Journal Issue: 6; Journal ID: ISSN 1539-3755
American Physical Society (APS)
Research Org:
Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
Sponsoring Org:
Country of Publication:
United States
97 MATHEMATICS AND COMPUTING extreme-value statistics