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

In texmex: Threshold exceedences and multivariate extremes

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.
n	Number of random numbers to simulate.
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.

Details

The functions were originally based on code due to Stuart Coles and which appears in the ismev package. The functions have been vectorized and tested.

Random number generation is done by inversion of the distribution function. Code written by Harry Southworth.

Author(s)

Janet E Heffernan, 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))

Example output

Loading required package: mvtnorm
Loading required package: ggplot2

texmex documentation built on May 2, 2019, 4:56 p.m.