dgev: Density, cumulative density, quantiles and random number...

In harrysouthworth/texmex: Statistical Modelling of Extreme Values

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.

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.

Author(s)

Harry Southworth

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))

harrysouthworth/texmex documentation built on March 8, 2024, 7:50 p.m.