Learn R Programming

texmex (version 2.1)

dgpd: 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.
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

Random number generation is done by transformation of a standard exponential.

Examples

Run this code
  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))

Run the code above in your browser using DataLab