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Extreme values statistical analysis library

version 1.1 (781 KB) by Guillaume Talbot
Library of functions for the statistical analysis of extreme values


Updated 31 May 2021

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This library provides many interesting tools for the analysis of extreme events.
1) Basic functions (density function, cumulative distribution function, inverse-cdf, random generator, parameter estimation) for many statistical distributions :
a) Generalized extreme value distribution
b) Gumbel distribution
c) Logistic distribution
d) Normal distribution
e) Uniform distribution
f) Exponential distribution (2 parameters)
g) Generalized logistic distribution
h) Generalized Pareto distribution
i) LogNormal distrubution (with 2 parameters)
j) LogNormal distribution (with 3-parameters)
k) Pearson 3 distribution
l) Log-Pearson 3 distribution
m) Gamma distribution
2) Annual maxima extraction tool from timeseries
3) Choosing the appropriate distribution
4) QQplots
5) Quantiles estimates with confidence interval
6) Akaike Information criterion and log-likelihood function
7) Finding the L-moments of a sample
The Matlab Statistical Toolbox isn't necessary
The fitting of the parameters is based on the L-moment method from Hosking and Wallis (1997) :
Hosking, J., & Wallis, J. (1997). Regional Frequency Analysis: An Approach Based on L-Moments. Cambridge: Cambridge University Press. doi:10.1017/CBO9780511529443

Cite As

Guillaume Talbot (2022). Extreme values statistical analysis library (, MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2018a
Compatible with any release
Platform Compatibility
Windows macOS Linux

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