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lmom (version 1.1)

cdfgev: Generalized extreme-value distribution

Description

Distribution function and quantile function of the generalized extreme-value distribution.

Usage

cdfgev(x, para = c(0, 1, 0))
quagev(f, para = c(0, 1, 0))

Arguments

x
Vector of quantiles.
f
Vector of probabilities.
para
Numeric vector containing the parameters of the distribution, in the order $\xi, \alpha, k$ (location, scale, shape).

Value

  • cdfgev gives the distribution function; quagev gives the quantile function.

Details

The generalized extreme-value distribution with location parameter $\xi$, scale parameter $\alpha$ and shape parameter $k$ has distribution function $$F(x)=\exp(-\exp(-y))$$ where $$y=-k^{-1}\log(1-k(x-\xi)/\alpha),$$ with $x$ bounded by $\xi+\alpha/k$ from below if $k<0$ and="" from="" above="" if="" $k="">0$, and quantile function $$x(F)=\xi-{\alpha\over k}(1-(-\log F)^k).$$ Extreme-value distribution types I, II and III (Gumbel, Frechet, Weibull) correspond to shape parameter values $k=0$, $k<0$ and="" $k="">0$ respectively.

See Also

cdfgum for the Gumbel (extreme-value type I) distribution. cdfkap for the kappa distribution, which generalizes the generalized extreme-value distribution. cdfwei for the Weibull distribution,

Examples

Run this code
# Random sample from the generalized extreme-value distribution
# with parameters xi=0, alpha=1, k=-0.5.
quagev(runif(100), c(0,1,-0.5))

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