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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

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)
QRM

Provides R-Language Code to Examine Quantitative Risk Management Concepts

v0.4-31
GPL (>= 2)
Authors
Bernhard Pfaff [aut, cre], Marius Hofert [ctb], Alexander McNeil [aut] (S-Plus original (QRMlib)), Scott Ulmann [trl] (First R port as package QRMlib)
Initial release
2020-02-15

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