Generalized Extreme Value Distribution

Fit, evaluate, and generate random samples from generalized extreme value distribution

Statistics and Machine Learning Toolbox™ offers multiple ways to work with the generalized extreme value distribution.

Create a GeneralizedExtremeValueDistribution object and use GeneralizedExtremeValueDistribution object functions.
Use distribution-specific functions with specified distribution parameters. The functions can accept parameters of multiple generalized extreme value distributions.
Use the generic distribution functions with the specified distribution name "Generalized Extreme Value" and corresponding parameters.

To learn about the generalized extreme value distribution, see Generalized Extreme Value Distribution.

Functions

`makedist`	Create probability distribution object
`fitdist`	Fit probability distribution object to data

`cdf`	Cumulative distribution function
`gather`	Gather properties of Statistics and Machine Learning Toolbox object from GPU (Since R2020b)
`icdf`	Inverse cumulative distribution function
`iqr`	Interquartile range of probability distribution
`mean`	Mean of probability distribution
`median`	Median of probability distribution
`negloglik`	Negative loglikelihood of probability distribution
`paramci`	Confidence intervals for probability distribution parameters
`pdf`	Probability density function
`plot`	Plot probability distribution object (Since R2022b)
`proflik`	Profile likelihood function for probability distribution
`random`	Random numbers
`std`	Standard deviation of probability distribution
`truncate`	Truncate probability distribution object
`var`	Variance of probability distribution

`gevcdf`	Generalized extreme value cumulative distribution function
`gevpdf`	Generalized extreme value probability density function
`gevinv`	Generalized extreme value inverse cumulative distribution function
`gevlike`	Generalized extreme value negative log-likelihood
`gevstat`	Generalized extreme value mean and variance
`gevfit`	Generalized extreme value parameter estimates
`gevrnd`	Generalized extreme value random numbers

`cdf`	Cumulative distribution function
`icdf`	Inverse cumulative distribution function
`pdf`	Probability density function
`random`	Random numbers
`mle`	Maximum likelihood estimates

GeneralizedExtremeValueDistribution Generalized extreme value probability distribution object

Fit probability distributions to data

Generalized Extreme Value Distribution
The generalized extreme value distribution is often used to model the smallest or largest value among a large set of independent, identically distributed random values representing measurements or observations.
Modeling Data with the Generalized Extreme Value Distribution
This example shows how to fit the generalized extreme value distribution using maximum likelihood estimation.