Extreme values statistical analysis library

버전 1.2.1 (782 KB) 작성자: Guillaume Talbot
Library of functions for the statistical analysis of extreme values
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업데이트 날짜: 2022/8/26

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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, except for the "example_xxx" scripts, where I use the "quantile.m" function. If not available, I recommend you download the "Quantiles" function by David Ferreira (https://www.mathworks.com/matlabcentral/fileexchange/70279-quantiles) and place it in your directory
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
Your comments/suggestions are welcome!

인용 양식

Guillaume Talbot (2024). Extreme values statistical analysis library (https://www.mathworks.com/matlabcentral/fileexchange/93075-extreme-values-statistical-analysis-library), MATLAB Central File Exchange. 검색됨 .

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버전 게시됨 릴리스 정보

Fixed some errors in the help sections of the Pearson 3 and Log-Pearson 3 distributions


-Added a correction factor for the Akaike Information Criterion
-Fixed a error for "lmoments_to_parameters.m"


a) Fixed a lot of typos in the help/comments
b) Fixed an important error with logpearson3.pdf
c) Added logistic, lognormal2 and gamma distributions
d) Added log_likelihood_extreme.m, akaike_extreme.m and lmoments_to_parameters.m