Related Experiment Video
Updated: Jul 4, 2026

Modeling the Size Spectrum for Macroinvertebrates and Fishes in Stream Ecosystems
Published on: July 30, 2019
Finite-size scaling in extreme statistics
G Györgyi1, N R Moloney, K Ozogány
1Institute for Theoretical Physics-HAS, Eötvös University, Pázmány sétány 1/a, 1117 Budapest, Hungary.
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/f;(alpha) stationary (alpha<1) noise, the iid shape correction compares favorably to simulations. Furthermore, for the strongly correlated regime (alpha>1) of 1/f;(alpha) noise, the shape correction is obtained in terms of the limit distribution itself.
Related Concept Videos
Limits at Infinity
Introduction to Scalers
Scalar...
Absolute and Local Extreme Values
Testing a Claim about Standard Deviation
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...
Distributions to Estimate Population Parameter
Chebyshev's Theorem to Interpret Standard Deviation

