QRM (version 0.4-7)

GEV: Generalized Extreme Value Distribution

Description

Density, quantiles, cumulative probability, and fitting of the Generalized Extreme Value distribution.

Usage

pGEV(q, xi, mu = 0, sigma = 1) 
qGEV(p, xi, mu = 0, sigma = 1) 
dGEV(x, xi, mu = 0, sigma = 1, log = FALSE) 
rGEV(n, xi, mu = 0, sigma = 1)
fit.GEV(maxima, ...)

Arguments

log

logical, whether log values of density should be returned, default is FALSE.

maxima

vector, block maxima data

mu

numeric, location parameter.

n

integer, count of random variates.

p

vector, probabilities.

q

vector, quantiles.

sigma

numeric, scale parameter.

x

vector, values to evaluate density.

xi

numeric, shape parameter.

...

ellipsis, arguments are passed down to optim().

Value

• numeric, probability (pGEV), quantile (qGEV), density (dGEV) or random variates (rGEV) for the GEV distribution with shape parameter $\xi$, location parameter $\mu$ and scale parameter $\sigma$. A list object in case of fit.GEV().

See Also

GPD

Examples

quantValue <- 4.5
pGEV(q = quantValue, xi = 0, mu = 1.0, sigma = 2.5) 
pGumbel(q = quantValue, mu = 1.0, sigma = 2.5)
## Fitting to monthly block-maxima
data(nasdaq)
l <- -returns(nasdaq)
em <- timeLastDayInMonth(time(l))
monmax <- aggregate(l, by = em, FUN = max) 
mod1 <- fit.GEV(monmax)