Finite-size scaling in extreme statistics

G. Györgyi, N. R. Moloney, K. Ozogány, Z. Rácz

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Abstract

We study the deviations from the limit distributions in extreme value statistics arising due to the finite size (FS) of data sets. A renormalization method is introduced for the case of independent, identically distributed (iid) variables, showing that the iid universality classes are subdivided according to the exponent of the FS convergence, which determines the leading order FS shape correction function as well. It is found that, for the correlated systems of subcritical percolation and 1/fα stationary (α<1) noise, the iid shape correction compares favorably to simulations. Furthermore, for the strongly correlated regime (α>1) of 1/fα noise, the shape correction is obtained in terms of the limit distribution itself.

Original languageEnglish
Article number210601
JournalPhysical review letters
Volume100
Issue number21
DOIs
Publication statusPublished - May 29 2008

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ASJC Scopus subject areas

  • Physics and Astronomy(all)

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