dgpd function

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

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

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.

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))

Author(s)

Janet E Heffernan, Paul Metcalfe, Harry Southworth