dgev: Density, cumulative density, quantiles and random number...
In texmex: Statistical Modelling of Extreme Values

Description Usage Arguments Details Author(s) Examples

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

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)

`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.

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

Harry Southworth

  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))