gev: GENERALIZED EXTREME VALUE DISTRIBUTION

In Rsafd: Statistical Analysis of Financial Data in R

Description

Density, cumulative distribution function, quantiles and random sample generation for the Generalized Extreme Value (GEV) distribution

Usage

         dgev(x, m=0, lambda = 1, xi = 0)    
         pgev(q, m=0, lambda = 1, xi = 0)
         qgev(p, m=0, lambda = 1, xi = 0)
         rgev(n, m=0, lambda = 1, xi = 0)

Arguments

x	numeric vector. Missing values (NA's) are allowed
q	vector of quantiles. Missing values (NA's) are allowed
p	vector of probabilities. Missing values (NA's) are allowed
n	sample size. If length(n) is larger than 1, then length(n) random values are returned
Optional Arguments
m	Location parameter. Can be a vector (see details)
lambda	Scale parameter. Can be a vector (see details)
xi	Shape parameter (note the sign convention described in SHAPE.XI). Can be a vector (see details)

Details

The length of vectors m, lambda, and xi should either be 1 or equal to the length of the vectors x, q, p, or n. Missing values and NA's are not allowed.

Value

Density (dgev), cumulative distribution function (pgev), quantile (qgev), or random sample (rgev) for the Generalized Pareto Distribution with parameters m, lambda, and xi.

SIDE EFFECTS The function rgpd causes the creation of .Random.seed if it does not already exist, otherwise its value is updated.

Author(s)

Rene Carmona, [e-mail]

References

R. A. Carmona: Statistical Analysis of Financial Data in S-Plus, (2004) Springer Verlag

See Also

rgev, gpd.lmom, gpd.ml

Examples

    x <- rgev(200) # Generates a sample of size 200 from
                   # the Gumbel distribution
    # Evaluation at x = 1.0 of GEV density functions
    # with different parameters
    m <- c(0,0,0)
    lambda <- c(1.3, 1.0, .7)
    xi <- c(-0.2,0.0,0.2)
    x <- rep(1.0,3)
    pgev(x,m,lambda,xi)
    

Rsafd documentation built on May 2, 2019, 5:20 p.m.