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

In texmex: Statistical Modelling of Extreme Values

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

Description

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

Usage

dgpd(x, sigma, xi, u = 0, log.d = FALSE)

pgpd(q, sigma, xi, u = 0, lower.tail = TRUE, log.p = FALSE)

qgpd(p, sigma, xi, u = 0, lower.tail = TRUE, log.p = FALSE)

rgpd(n, sigma, xi, u = 0)

Arguments

x, q, p	Value, quantile or probability respectively.
sigma	Scale parameter.
xi	Shape parameter.
u	Threshold
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 by transformation of a standard exponential.

Author(s)

Janet E Heffernan, Paul Metcalfe, Harry Southworth

Examples

  x <- rgpd(1000, sigma=1, xi=.5)
  hist(x)
  x <- rgpd(1000, sigma=exp(rnorm(1000, 1, .25)), xi=rnorm(1000, .5, .2))
  hist(x)
  plot(pgpd(x, sigma=1, xi=.5))

texmex documentation built on June 22, 2024, 12:26 p.m.