texmex (version 2.4.9)

dgev: Density, cumulative density, quantiles and random number generation for the generalized extreme value distribution

Description

Density, cumulative density, quantiles and random number generation for the generalized extreme value distribution

Usage

dgev(x, mu, sigma, xi, log.d = FALSE)
pgev(q, mu, sigma, xi, lower.tail = TRUE, log.p = FALSE)
qgev(p, mu, sigma, xi, lower.tail = TRUE, log.p = FALSE)
rgev(n, mu, sigma, xi)

Arguments

x, q, p

Value, quantile or probability respectively.

mu

Location parameter.

sigma

Scale parameter.

xi

Shape parameter.

log.d, log.p

Whether or not to work on the log scale.

lower.tail

Whether to return the lower tail.

n

Number of random numbers to simulate.

Author

Harry Southworth

Details

Random number generation is done as a transformation of the Gumbel distribution; Gumbel random variates are generated as the negative logarithm of standard exponentials.

Examples

  x <- rgev(1000, mu=0, sigma=1, xi=.5)
  hist(x)
  x <- rgev(1000, mu=0, sigma=exp(rnorm(1000, 1, .25)), xi=rnorm(1000, .5, .2))
  hist(x)
  plot(pgev(x, mu=0, sigma=1, xi=.5))