dGEV: The Generalized Extreme Value Distribution

In ExtremalDep: Extremal Dependence Models

The Generalized Extreme Value Distribution

Description

Density, distribution and quantile function for the Generalized Extreme Value (GEV) distribution.

Usage

dGEV(x, loc, scale, shape, log=FALSE)
pGEV(q, loc, scale, shape, lower.tail=TRUE)
qGEV(p, loc, scale, shape)

Arguments

x, q	vector of quantiles.
p	vector of probabilities.
loc	vector of locations.
scale	vector of scales.
shape	vector of shapes.
log	A logical value; if TRUE returns the log density.
lower.tail	A logical value; if TRUE probabilities are P(X≤q x), otherwise P(X > x).

Details

The GEV distribution has density

f(x; μ,σ,ξ) = exp { -[1 + ξ ( (x-μ)/σ )]_+^(-1/ξ) }

Value

density (dGEV), distribution function (pGEV) and quantile function (qGEV) from the Generalized Extreme Value distirbution with given location, scale and shape.

Author(s)

Simone Padoan, [e-mail], https://faculty.unibocconi.it/simonepadoan/; Boris Beranger, [e-mail] https://www.borisberanger.com;

See Also

fGEV

Examples

# Densities
dGEV(x=1, loc=1, scale=1, shape=1)
dGEV(x=c(0.2, 0.5), loc=1, scale=1, shape=c(0,0.3))

# Probabilities
pGEV(q=1, loc=1, scale=1, shape=1, lower.tail=FALSE)
pGEV(q=c(0.2, 0.5), loc=1, scale=1, shape=c(0,0.3))

# Quantiles
qGEV(p=0.5, loc=1, scale=1, shape=1)
qGEV(p=c(0.2, 0.5), loc=1, scale=1, shape=c(0,0.3))

ExtremalDep documentation built on March 7, 2023, 3:16 p.m.